TIMEOUT

The TRS could not be proven terminating. The proof attempt took 60000 ms.

The following DP Processors were used


Problem 1 was processed with processor DependencyGraph (31ms).
 | – Problem 2 was processed with processor ForwardNarrowing (2ms).
 |    | – Problem 4 was processed with processor ForwardNarrowing (2ms).
 |    |    | – Problem 5 was processed with processor ForwardNarrowing (1ms).
 |    |    |    | – Problem 6 was processed with processor ForwardNarrowing (3ms).
 |    |    |    |    | – Problem 7 was processed with processor ForwardNarrowing (1ms).
 |    |    |    |    |    | – Problem 8 was processed with processor ForwardNarrowing (1ms).
 |    |    |    |    |    |    | – Problem 9 was processed with processor ForwardInstantiation (5ms).
 |    |    |    |    |    |    |    | – Problem 10 was processed with processor Propagation (7ms).
 |    |    |    |    |    |    |    |    | – Problem 11 was processed with processor ForwardNarrowing (4ms).
 |    |    |    |    |    |    |    |    |    | – Problem 12 was processed with processor ForwardNarrowing (2ms).
 |    |    |    |    |    |    |    |    |    |    | – Problem 13 was processed with processor ForwardNarrowing (2ms).
 |    |    |    |    |    |    |    |    |    |    |    | – Problem 14 was processed with processor ForwardNarrowing (1ms).
 |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 15 was processed with processor ForwardNarrowing (1ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 16 was processed with processor ForwardNarrowing (3ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 17 was processed with processor ForwardNarrowing (2ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 18 was processed with processor ForwardNarrowing (1ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 19 was processed with processor ForwardNarrowing (4ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 20 was processed with processor ForwardNarrowing (4ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 21 was processed with processor ForwardNarrowing (3ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 22 was processed with processor ForwardNarrowing (3ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 23 was processed with processor ForwardNarrowing (2ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 24 was processed with processor ForwardNarrowing (1ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 25 was processed with processor ForwardNarrowing (3ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 26 was processed with processor ForwardNarrowing (5ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 27 was processed with processor ForwardNarrowing (2ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 28 was processed with processor ForwardNarrowing (3ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 29 was processed with processor ForwardNarrowing (2ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 30 was processed with processor ForwardNarrowing (5ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 31 was processed with processor ForwardNarrowing (12ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 32 was processed with processor ForwardNarrowing (17ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 33 was processed with processor ForwardNarrowing (27ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 34 was processed with processor ForwardNarrowing (39ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 35 was processed with processor ForwardNarrowing (8ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 36 was processed with processor ForwardNarrowing (57ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 37 was processed with processor ForwardNarrowing (63ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 38 was processed with processor ForwardNarrowing (77ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 39 was processed with processor ForwardNarrowing (118ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 40 was processed with processor ForwardNarrowing (148ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 41 was processed with processor ForwardNarrowing (183ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 42 was processed with processor ForwardNarrowing (123ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 43 was processed with processor ForwardNarrowing (111ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 44 was processed with processor ForwardNarrowing (198ms).
 |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    |    | – Problem 45 remains open; application of the following processors failed [ForwardNarrowing (149ms), ForwardNarrowing (146ms), ForwardNarrowing (227ms), ForwardNarrowing (146ms), ForwardNarrowing (143ms), ForwardNarrowing (135ms), ForwardNarrowing (132ms), ForwardNarrowing (125ms), ForwardNarrowing (228ms), ForwardNarrowing (139ms), ForwardNarrowing (timeout)].
 | – Problem 3 was processed with processor SubtermCriterion (1ms).

The following open problems remain:

Open Dependency Pair Problem 2

Dependency Pairs

length#(cons(N, L)) → length#(activate(L))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Problem 1: DependencyGraph

Dependency Pair Problem

Dependency Pairs

length#(cons(N, L)) → length#(activate(L))and#(tt, X) → activate#(X)
activate#(n__zeros) → zeros#activate#(n__take(X1, X2)) → take#(X1, X2)
take#(s(M), cons(N, IL)) → activate#(IL)length#(cons(N, L)) → activate#(L)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The following SCCs where found

length#(cons(N, L)) → length#(activate(L))
activate#(n__take(X1, X2)) → take#(X1, X2)take#(s(M), cons(N, IL)) → activate#(IL)

Problem 2: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, L)) → length#(activate(L))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, L)) → length#(activate(L)) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(_x21) 
length#(take(_x21, _x22)) 
length#(zeros) 
Thus, the rule length#(cons(N, L)) → length#(activate(L)) is replaced by the following rules:
length#(cons(N, n__zeros)) → length#(zeros)length#(cons(N, n__take(_x21, _x22))) → length#(take(_x21, _x22))
length#(cons(N, _x21)) → length#(_x21)

Problem 4: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, n__zeros)) → length#(zeros)length#(cons(N, n__take(_x21, _x22))) → length#(take(_x21, _x22))
length#(cons(N, _x21)) → length#(_x21)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, n__take(_x21, _x22))) → length#(take(_x21, _x22)) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, activate(_x31)))) 
length#(nil) 
length#(n__take(_x31, _x32)) 
Thus, the rule length#(cons(N, n__take(_x21, _x22))) → length#(take(_x21, _x22)) is replaced by the following rules:
length#(cons(N, n__take(_x31, _x32))) → length#(n__take(_x31, _x32))length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))
length#(cons(N, n__take(0, _x31))) → length#(nil)

Problem 5: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, n__take(_x31, _x32))) → length#(n__take(_x31, _x32))length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))
length#(cons(N, n__take(0, _x31))) → length#(nil)length#(cons(N, _x21)) → length#(_x21)
length#(cons(N, n__zeros)) → length#(zeros)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, n__take(_x31, _x32))) → length#(n__take(_x31, _x32)) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, n__take(_x31, _x32))) → length#(n__take(_x31, _x32)) is deleted.

Problem 6: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))length#(cons(N, n__take(0, _x31))) → length#(nil)
length#(cons(N, n__zeros)) → length#(zeros)length#(cons(N, _x21)) → length#(_x21)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, n__take(0, _x31))) → length#(nil) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, n__take(0, _x31))) → length#(nil) is deleted.

Problem 7: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))length#(cons(N, _x21)) → length#(_x21)
length#(cons(N, n__zeros)) → length#(zeros)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, n__zeros)) → length#(zeros) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(n__zeros) 
length#(cons(0, n__zeros)) 
Thus, the rule length#(cons(N, n__zeros)) → length#(zeros) is replaced by the following rules:
length#(cons(N, n__zeros)) → length#(cons(0, n__zeros))length#(cons(N, n__zeros)) → length#(n__zeros)

Problem 8: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))length#(cons(N, n__zeros)) → length#(cons(0, n__zeros))
length#(cons(N, _x21)) → length#(_x21)length#(cons(N, n__zeros)) → length#(n__zeros)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, n__zeros)) → length#(n__zeros) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, n__zeros)) → length#(n__zeros) is deleted.

Problem 9: ForwardInstantiation

Dependency Pair Problem

Dependency Pairs

length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))length#(cons(N, n__zeros)) → length#(cons(0, n__zeros))
length#(cons(N, _x21)) → length#(_x21)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

Instantiation

For all potential successors l → r of the rule length#(cons(N, _x21)) → length#(_x21) on dependency pair chains it holds that: Thus, length#(cons(N, _x21)) → length#(_x21) is replaced by instances determined through the above matching. These instances are:
length#(cons(N, cons(N, n__zeros))) → length#(cons(N, n__zeros))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(N, n__take(s(_x32), cons(_x33, _x31))))
length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))

Problem 10: Propagation

Dependency Pair Problem

Dependency Pairs

length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))length#(cons(N, cons(N, n__zeros))) → length#(cons(N, n__zeros))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(N, n__take(s(_x32), cons(_x33, _x31))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, n__zeros)) → length#(cons(0, n__zeros))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The dependency pairs length#(cons(N, cons(N, n__zeros))) → length#(cons(N, n__zeros)) and length#(cons(N, n__zeros)) → length#(cons(0, n__zeros)) are consolidated into the rule length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros)) .

This is possible as

The dependency pairs length#(cons(N, cons(N, n__zeros))) → length#(cons(N, n__zeros)) and length#(cons(N, n__zeros)) → length#(cons(0, n__zeros)) are consolidated into the rule length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros)) .

This is possible as

The dependency pairs length#(cons(N, cons(N, n__zeros))) → length#(cons(N, n__zeros)) and length#(cons(N, n__zeros)) → length#(cons(0, n__zeros)) are consolidated into the rule length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros)) .

This is possible as

The dependency pairs length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) and length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31)))) are consolidated into the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(_x33, n__take(_x32, activate(_x31)))) .

This is possible as

Summary

Removed Dependency PairsAdded Dependency Pairs
length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) → length#(cons(_x33, n__take(_x32, activate(_x31))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(_x33, n__take(_x32, activate(_x31))))
length#(cons(N, cons(N, n__zeros))) → length#(cons(N, n__zeros))length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(N, n__take(s(_x32), cons(_x33, _x31)))) 
length#(cons(N, n__zeros)) → length#(cons(0, n__zeros)) 

Problem 11: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(_x33, n__take(_x32, activate(_x31))))
length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(_x33, n__take(_x32, activate(_x31)))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, zeros))) 
length#(cons(_x33, n__take(_x32, _x61))) 
length#(cons(_x33, n__take(_x32, take(_x61, _x62)))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x31))))) → length#(cons(_x33, n__take(_x32, activate(_x31)))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, zeros)))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61)))

Problem 12: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, zeros)))
length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61)))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, zeros))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(0, n__zeros)))) 
length#(cons(_x33, n__take(_x32, n__zeros))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, zeros))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, cons(0, n__zeros))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, n__zeros)))

Problem 13: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, cons(0, n__zeros))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, n__zeros)))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61)))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62))))length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, cons(0, n__zeros)))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, cons(0, n__zeros)))) is deleted.

Problem 14: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, n__zeros)))
length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61)))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, n__zeros))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__zeros))))) → length#(cons(_x33, n__take(_x32, n__zeros))) is deleted.

Problem 15: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61)))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62))))length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros)) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__zeros))) → length#(cons(0, n__zeros)) is deleted.

Problem 16: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61)))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, _x61))))) → length#(cons(_x33, n__take(_x32, _x61))) is deleted.

Problem 17: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62)))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, n__take(_x71, _x72)))) 
length#(cons(_x33, n__take(_x32, nil))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, activate(_x71)))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x61, _x62)))))) → length#(cons(_x33, n__take(_x32, take(_x61, _x62)))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x71, _x72)))))) → length#(cons(_x33, n__take(_x32, n__take(_x71, _x72))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x71))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, activate(_x71))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil)))

Problem 18: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x71, _x72)))))) → length#(cons(_x33, n__take(_x32, n__take(_x71, _x72))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x71))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, activate(_x71))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil)))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x71, _x72)))))) → length#(cons(_x33, n__take(_x32, n__take(_x71, _x72)))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(_x71, _x72)))))) → length#(cons(_x33, n__take(_x32, n__take(_x71, _x72)))) is deleted.

Problem 19: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x71))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, activate(_x71))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil)))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x71))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, activate(_x71)))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102)))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, zeros))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x71))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, activate(_x71)))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, zeros)))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102))))))

Problem 20: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, zeros)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil)))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, zeros))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__zeros))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(0, n__zeros)))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, zeros))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(0, n__zeros))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__zeros)))))

Problem 21: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(0, n__zeros))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil)))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__zeros)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101)))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(0, n__zeros)))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(0, n__zeros)))))) is deleted.

Problem 22: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil)))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__zeros)))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(0, _x71)))))) → length#(cons(_x33, n__take(_x32, nil))) is deleted.

Problem 23: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__zeros)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101)))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__zeros))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__zeros))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__zeros))))) is deleted.

Problem 24: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, _x101))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, _x101))))) is deleted.

Problem 25: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102)))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, activate(_x111)))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__take(_x111, _x112)))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, nil))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x101, _x102)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, take(_x101, _x102)))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(0, _x111)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, nil)))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x111))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, activate(_x111))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x111, _x112)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__take(_x111, _x112))))))

Problem 26: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(0, _x111)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, nil)))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x111))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, activate(_x111))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x111, _x112)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__take(_x111, _x112))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(0, _x111)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, nil))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(0, _x111)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, nil))))) is deleted.

Problem 27: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x111))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, activate(_x111))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x111, _x112)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__take(_x111, _x112))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x111))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, activate(_x111)))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, take(_x141, _x142)))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, zeros))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, _x141))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x111))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, activate(_x111)))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x141))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, _x141)))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(_x141, _x142)))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, take(_x141, _x142))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__zeros))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, zeros)))))))

Problem 28: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x141))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, _x141)))))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(_x141, _x142)))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, take(_x141, _x142))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__zeros))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, zeros)))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x111, _x112)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__take(_x111, _x112))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x141))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, _x141))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, _x141))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, _x141))))))) is deleted.

Problem 29: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(_x141, _x142)))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, take(_x141, _x142))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__zeros))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, zeros)))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x111, _x112)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__take(_x111, _x112))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(_x141, _x142)))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, take(_x141, _x142)))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, nil))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, activate(_x151)))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, n__take(_x151, _x152)))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(_x141, _x142)))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, take(_x141, _x142)))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, _x151))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, activate(_x151))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(0, _x151)))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, nil)))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(_x151, _x152)))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, n__take(_x151, _x152))))))))

Problem 30: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(0, _x331)))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, nil)))))))))))))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, _x331))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, activate(_x331))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__zeros))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(0, n__zeros))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(_x111, _x112)))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, n__take(_x111, _x112))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__zeros))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(0, n__zeros))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__zeros))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(0, n__zeros))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, _x221))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, _x221)))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(_x291, _x292)))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, n__take(_x291, _x292))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, _x181))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, _x181)))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(0, _x331)))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, nil))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(0, _x331)))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, nil))))))))))))))) is deleted.

Problem 31: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__zeros))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, n__zeros)))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, _x221))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, _x221)))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__zeros))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(0, n__zeros))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__zeros))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, n__zeros)))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__zeros))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, n__zeros)))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, _x651))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, activate(_x651))))))))))))))))))))))))))))))))
length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(_x651, _x652)))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, n__take(_x651, _x652))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, _x621))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, _x621)))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__zeros))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(0, n__zeros))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__zeros))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(0, n__zeros))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, _x181))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, _x181)))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(_x291, _x292)))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, n__take(_x291, _x292))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__zeros))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, zeros)))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__zeros))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, n__zeros))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__zeros))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, n__zeros))))))))))))))))))))))))))))) is deleted.

Problem 32: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__zeros))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, n__zeros)))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(_x871, _x872)))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, n__take(_x871, _x872))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__zeros))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, n__zeros)))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, _x911))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, activate(_x911))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, _x801))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, _x801)))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, _x861))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, _x861)))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__zeros))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(0, n__zeros))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__zeros))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(0, n__zeros))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(_x291, _x292)))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, n__take(_x291, _x292))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__zeros))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, zeros)))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, _x181))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, _x181)))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(_x871, _x872)))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, n__take(_x871, _x872)))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(_x871, _x872)))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, n__take(_x871, _x872)))))))))))))))))))))))))))))))))))))))) is deleted.

Problem 33: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, _x1171))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, activate(_x1171))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(0, _x1171)))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(_x1131, _x1132)))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, n__take(_x1131, _x1132))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(_x291, _x292)))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, n__take(_x291, _x292))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, _x181))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, _x181)))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__zeros))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, zeros)))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, _x1171))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, activate(_x1171)))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, take(_x1201, _x1202)))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, _x1201))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, _x1171))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, activate(_x1171)))))))))))))))))))))))))))))))))))))))))))))))))))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(_x1201, _x1202)))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, take(_x1201, _x1202))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, _x1201))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, _x1201)))))))))))))))))))))))))))))))))))))))))))))))))))))))

Problem 34: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(_x1481, _x1482)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, take(_x1481, _x1482))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, _x1481))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, _x1481)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(_x1451, _x1452)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, n__take(_x1451, _x1452))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(0, _x1451)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__zeros))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, zeros)))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(0, _x1231)))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(_x1481, _x1482)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, take(_x1481, _x1482)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, activate(_x1491)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, n__take(_x1491, _x1492)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, nil))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(_x1481, _x1482)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, take(_x1481, _x1482)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, _x1491))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, activate(_x1491))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(_x1491, _x1492)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, n__take(_x1491, _x1492))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(0, _x1491)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Problem 35: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__zeros))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(0, n__zeros))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(0, _x1451)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(0, _x1231)))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(_x1701, _x1702)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, take(_x1701, _x1702))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__zeros))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(0, n__zeros)))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__zeros))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(0, n__zeros)))))))))))))))))))))))))) is deleted.

Problem 36: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(0, _x2031)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, _x2001))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, _x2001)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(_x2061, _x2062)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, take(_x2061, _x2062))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(0, _x1231)))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(_x2031, _x2032)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, n__take(_x2031, _x2032))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, _x1921))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, _x1921)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(_x1791, _x1792)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, n__take(_x1791, _x1792))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(0, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(0, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is deleted.

Problem 37: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(_x2291, _x2292)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, n__take(_x2291, _x2292))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(0, _x2291)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(_x2321, _x2322)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, take(_x2321, _x2322))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, _x2321))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, _x2321)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, _x2101))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, _x2101)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(_x2031, _x2032)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, n__take(_x2031, _x2032))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(_x1791, _x1792)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, n__take(_x1791, _x1792))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, _x1921))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, _x1921)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(0, _x1231)))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is deleted.

Problem 38: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, _x2551))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, activate(_x2551))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(0, _x2511)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, _x1921))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, _x1921)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(_x1791, _x1792)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, n__take(_x1791, _x1792))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(_x2031, _x2032)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, n__take(_x2031, _x2032))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, _x2551))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, activate(_x2551)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, _x2581))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, take(_x2581, _x2582)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, _x2551))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, activate(_x2551)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, _x2581))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, _x2581)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(_x2581, _x2582)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, take(_x2581, _x2582))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Problem 39: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(_x2921, _x2922)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, take(_x2921, _x2922))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(0, _x2891)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(_x2851, _x2852)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, n__take(_x2851, _x2852))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, _x2721))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, _x2721)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, _x2761))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, _x2761)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(0, _x2511)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, _x2801))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, _x2801)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, _x1921))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, _x1921)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(_x1791, _x1792)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, n__take(_x1791, _x1792))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(_x2031, _x2032)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, n__take(_x2031, _x2032))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(_x2921, _x2922)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, take(_x2921, _x2922)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, nil))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, n__take(_x2931, _x2932)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, activate(_x2931)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(_x2921, _x2922)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, take(_x2921, _x2922)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(0, _x2931)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(_x2931, _x2932)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, n__take(_x2931, _x2932))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, _x2931))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, activate(_x2931))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Problem 40: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, _x2801))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, _x2801)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(_x1791, _x1792)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, n__take(_x1791, _x1792))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(_x3011, _x3012)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, n__take(_x3011, _x3012))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, _x3091))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, activate(_x3091))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, _x3091))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, activate(_x3091)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, take(_x3121, _x3122)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, _x3121))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, _x3091))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, activate(_x3091)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, _x3121))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, _x3121)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(_x3121, _x3122)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, take(_x3121, _x3122))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Problem 41: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(0, _x3311)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(0, _x3391)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(0, _x3351)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(_x3481, _x3482)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, take(_x3481, _x3482))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, _x3181))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, _x3181)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, _x3301))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, _x3301)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(_x3011, _x3012)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, n__take(_x3011, _x3012))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(_x1791, _x1792)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, n__take(_x1791, _x1792))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, _x2801))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, _x2801)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(0, _x3311)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, nil))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(0, _x3311)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, nil))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is deleted.

Problem 42: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(_x3531, _x3532)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, n__take(_x3531, _x3532))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, _x3301))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, _x3301)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, _x3181))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, _x3181)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(_x1791, _x1792)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, n__take(_x1791, _x1792))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, _x3711))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, activate(_x3711))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(_x3011, _x3012)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, n__take(_x3011, _x3012))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, _x2801))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, _x2801)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(_x3531, _x3532)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, n__take(_x3531, _x3532)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(_x3531, _x3532)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, n__take(_x3531, _x3532)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is deleted.

Problem 43: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(_x3921, _x3922)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, take(_x3921, _x3922))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(_x3891, _x3892)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, n__take(_x3891, _x3892))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, _x3881))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, _x3881)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(0, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(_x3891, _x3892)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, n__take(_x3891, _x3892)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(_x3891, _x3892)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, n__take(_x3891, _x3892)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is deleted.

Problem 44: ForwardNarrowing

Dependency Pair Problem

Dependency Pairs

length#(cons(N, cons(_N, __x21))) → length#(cons(_N, __x21))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(0, _x4191)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(s(_x4192), cons(_x4193, n__take(_x4221, _x4222)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, take(_x4221, _x4222))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(s(_x4192), cons(_x4193, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, _x4181))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, _x4181)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__zeros))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, n__zeros)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(_x4151, _x4152)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, n__take(_x4151, _x4152))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(_x4111, _x4112)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, n__take(_x4111, _x4112))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, _x4101))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, _x4101)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, tt, zeros, take, length, n__take, n__zeros, nil, and, cons

Strategy

The right-hand side of the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(s(_x4192), cons(_x4193, n__take(_x4221, _x4222)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, take(_x4221, _x4222)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is narrowed to the following relevant and irrelevant terms (a narrowing is irrelevant if by dropping it the correctness (and completeness) of the processor is not influenced).
Relevant TermsIrrelevant Terms
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, nil))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, n__take(_x4251, _x4252)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, cons(_x4253, n__take(_x4252, activate(_x4251)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) 
Thus, the rule length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(s(_x4192), cons(_x4193, n__take(_x4221, _x4222)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, take(_x4221, _x4222)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) is replaced by the following rules:
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(s(_x4192), cons(_x4193, n__take(0, _x4251)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, nil)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(s(_x4192), cons(_x4193, n__take(_x4251, _x4252)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, n__take(_x4251, _x4252))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
length#(cons(N, cons(N, n__take(s(_x32), cons(_x33, n__take(s(_x72), cons(_x73, n__take(s(_x112), cons(_x113, n__take(s(_x152), cons(_x153, n__take(s(_x192), cons(_x193, n__take(s(_x252), cons(_x253, n__take(s(_x292), cons(_x293, n__take(s(_x332), cons(_x333, n__take(s(_x372), cons(_x373, n__take(s(_x432), cons(_x433, n__take(s(_x472), cons(_x473, n__take(s(_x512), cons(_x513, n__take(s(_x552), cons(_x553, n__take(s(_x592), cons(_x593, n__take(s(_x652), cons(_x653, n__take(s(_x692), cons(_x693, n__take(s(_x732), cons(_x733, n__take(s(_x772), cons(_x773, n__take(s(_x832), cons(_x833, n__take(s(_x872), cons(_x873, n__take(s(_x912), cons(_x913, n__take(s(_x952), cons(_x953, n__take(s(_x992), cons(_x993, n__take(s(_x1052), cons(_x1053, n__take(s(_x1092), cons(_x1093, n__take(s(_x1132), cons(_x1133, n__take(s(_x1172), cons(_x1173, n__take(s(_x1232), cons(_x1233, n__take(s(_x1272), cons(_x1273, n__take(s(_x1312), cons(_x1313, n__take(s(_x1352), cons(_x1353, n__take(s(_x1392), cons(_x1393, n__take(s(_x1452), cons(_x1453, n__take(s(_x1492), cons(_x1493, n__take(s(_x1532), cons(_x1533, n__take(s(_x1572), cons(_x1573, n__take(s(_x1632), cons(_x1633, n__take(s(_x1672), cons(_x1673, n__take(s(_x1712), cons(_x1713, n__take(s(_x1752), cons(_x1753, n__take(s(_x1792), cons(_x1793, n__take(s(_x1852), cons(_x1853, n__take(s(_x1892), cons(_x1893, n__take(s(_x1932), cons(_x1933, n__take(s(_x1972), cons(_x1973, n__take(s(_x2032), cons(_x2033, n__take(s(_x2072), cons(_x2073, n__take(s(_x2112), cons(_x2113, n__take(s(_x2152), cons(_x2153, n__take(s(_x2192), cons(_x2193, n__take(s(_x2252), cons(_x2253, n__take(s(_x2292), cons(_x2293, n__take(s(_x2332), cons(_x2333, n__take(s(_x2372), cons(_x2373, n__take(s(_x2432), cons(_x2433, n__take(s(_x2472), cons(_x2473, n__take(s(_x2512), cons(_x2513, n__take(s(_x2552), cons(_x2553, n__take(s(_x2592), cons(_x2593, n__take(s(_x2652), cons(_x2653, n__take(s(_x2692), cons(_x2693, n__take(s(_x2732), cons(_x2733, n__take(s(_x2772), cons(_x2773, n__take(s(_x2852), cons(_x2853, n__take(s(_x2892), cons(_x2893, n__take(s(_x2932), cons(_x2933, n__take(s(_x2972), cons(_x2973, n__take(s(_x3012), cons(_x3013, n__take(s(_x3052), cons(_x3053, n__take(s(_x3092), cons(_x3093, n__take(s(_x3152), cons(_x3153, n__take(s(_x3192), cons(_x3193, n__take(s(_x3232), cons(_x3233, n__take(s(_x3272), cons(_x3273, n__take(s(_x3312), cons(_x3313, n__take(s(_x3352), cons(_x3353, n__take(s(_x3392), cons(_x3393, n__take(s(_x3452), cons(_x3453, n__take(s(_x3492), cons(_x3493, n__take(s(_x3532), cons(_x3533, n__take(s(_x3572), cons(_x3573, n__take(s(_x3632), cons(_x3633, n__take(s(_x3672), cons(_x3673, n__take(s(_x3712), cons(_x3713, n__take(s(_x3752), cons(_x3753, n__take(s(_x3792), cons(_x3793, n__take(s(_x3852), cons(_x3853, n__take(s(_x3892), cons(_x3893, n__take(s(_x3932), cons(_x3933, n__take(s(_x3972), cons(_x3973, n__take(s(_x4032), cons(_x4033, n__take(s(_x4072), cons(_x4073, n__take(s(_x4112), cons(_x4113, n__take(s(_x4152), cons(_x4153, n__take(s(_x4192), cons(_x4193, n__take(s(_x4252), cons(_x4253, _x4251))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) → length#(cons(_x33, n__take(_x32, cons(_x73, n__take(_x72, cons(_x113, n__take(_x112, cons(_x153, n__take(_x152, cons(_x193, n__take(_x192, cons(_x253, n__take(_x252, cons(_x293, n__take(_x292, cons(_x333, n__take(_x332, cons(_x373, n__take(_x372, cons(_x433, n__take(_x432, cons(_x473, n__take(_x472, cons(_x513, n__take(_x512, cons(_x553, n__take(_x552, cons(_x593, n__take(_x592, cons(_x653, n__take(_x652, cons(_x693, n__take(_x692, cons(_x733, n__take(_x732, cons(_x773, n__take(_x772, cons(_x833, n__take(_x832, cons(_x873, n__take(_x872, cons(_x913, n__take(_x912, cons(_x953, n__take(_x952, cons(_x993, n__take(_x992, cons(_x1053, n__take(_x1052, cons(_x1093, n__take(_x1092, cons(_x1133, n__take(_x1132, cons(_x1173, n__take(_x1172, cons(_x1233, n__take(_x1232, cons(_x1273, n__take(_x1272, cons(_x1313, n__take(_x1312, cons(_x1353, n__take(_x1352, cons(_x1393, n__take(_x1392, cons(_x1453, n__take(_x1452, cons(_x1493, n__take(_x1492, cons(_x1533, n__take(_x1532, cons(_x1573, n__take(_x1572, cons(_x1633, n__take(_x1632, cons(_x1673, n__take(_x1672, cons(_x1713, n__take(_x1712, cons(_x1753, n__take(_x1752, cons(_x1793, n__take(_x1792, cons(_x1853, n__take(_x1852, cons(_x1893, n__take(_x1892, cons(_x1933, n__take(_x1932, cons(_x1973, n__take(_x1972, cons(_x2033, n__take(_x2032, cons(_x2073, n__take(_x2072, cons(_x2113, n__take(_x2112, cons(_x2153, n__take(_x2152, cons(_x2193, n__take(_x2192, cons(_x2253, n__take(_x2252, cons(_x2293, n__take(_x2292, cons(_x2333, n__take(_x2332, cons(_x2373, n__take(_x2372, cons(_x2433, n__take(_x2432, cons(_x2473, n__take(_x2472, cons(_x2513, n__take(_x2512, cons(_x2553, n__take(_x2552, cons(_x2593, n__take(_x2592, cons(_x2653, n__take(_x2652, cons(_x2693, n__take(_x2692, cons(_x2733, n__take(_x2732, cons(_x2773, n__take(_x2772, cons(_x2853, n__take(_x2852, cons(_x2893, n__take(_x2892, cons(_x2933, n__take(_x2932, cons(_x2973, n__take(_x2972, cons(_x3013, n__take(_x3012, cons(_x3053, n__take(_x3052, cons(_x3093, n__take(_x3092, cons(_x3153, n__take(_x3152, cons(_x3193, n__take(_x3192, cons(_x3233, n__take(_x3232, cons(_x3273, n__take(_x3272, cons(_x3313, n__take(_x3312, cons(_x3353, n__take(_x3352, cons(_x3393, n__take(_x3392, cons(_x3453, n__take(_x3452, cons(_x3493, n__take(_x3492, cons(_x3533, n__take(_x3532, cons(_x3573, n__take(_x3572, cons(_x3633, n__take(_x3632, cons(_x3673, n__take(_x3672, cons(_x3713, n__take(_x3712, cons(_x3753, n__take(_x3752, cons(_x3793, n__take(_x3792, cons(_x3853, n__take(_x3852, cons(_x3893, n__take(_x3892, cons(_x3933, n__take(_x3932, cons(_x3973, n__take(_x3972, cons(_x4033, n__take(_x4032, cons(_x4073, n__take(_x4072, cons(_x4113, n__take(_x4112, cons(_x4153, n__take(_x4152, cons(_x4193, n__take(_x4192, cons(_x4253, n__take(_x4252, activate(_x4251))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Problem 3: SubtermCriterion

Dependency Pair Problem

Dependency Pairs

activate#(n__take(X1, X2)) → take#(X1, X2)take#(s(M), cons(N, IL)) → activate#(IL)

Rewrite Rules

zeros → cons(0, n__zeros)and(tt, X) → activate(X)
length(nil) → 0length(cons(N, L)) → s(length(activate(L)))
take(0, IL) → niltake(s(M), cons(N, IL)) → cons(N, n__take(M, activate(IL)))
zeros → n__zerostake(X1, X2) → n__take(X1, X2)
activate(n__zeros) → zerosactivate(n__take(X1, X2)) → take(X1, X2)
activate(X) → X

Original Signature

Termination of terms over the following signature is verified: activate, 0, s, zeros, tt, take, length, n__take, n__zeros, cons, and, nil

Strategy

Projection

The following projection was used:

Thus, the following dependency pairs are removed:

activate#(n__take(X1, X2)) → take#(X1, X2)take#(s(M), cons(N, IL)) → activate#(IL)