YES We show the termination of the TRS R: app(app(app(f(),|0|()),|1|()),x) -> app(app(app(f(),app(s(),x)),x),x) app(app(app(f(),x),y),app(s(),z)) -> app(s(),app(app(app(f(),|0|()),|1|()),z)) app(app(map(),|fun|),nil()) -> nil() app(app(map(),|fun|),app(app(cons(),x),xs)) -> app(app(cons(),app(|fun|,x)),app(app(map(),|fun|),xs)) app(app(filter(),|fun|),nil()) -> nil() app(app(filter(),|fun|),app(app(cons(),x),xs)) -> app(app(app(app(filter2(),app(|fun|,x)),|fun|),x),xs) app(app(app(app(filter2(),true()),|fun|),x),xs) -> app(app(cons(),x),app(app(filter(),|fun|),xs)) app(app(app(app(filter2(),false()),|fun|),x),xs) -> app(app(filter(),|fun|),xs) Instead we prove termination of the uncurried system: app(cons_0(),y) -> cons_1(y) app(cons_1(x1),y) -> cons_2(x1,y) app(f_0(),y) -> f_1(y) app(f_1(x1),y) -> f_2(x1,y) app(f_2(x1,x2),y) -> f_3(x1,x2,y) app(filter_0(),y) -> filter_1(y) app(filter_1(x1),y) -> filter_2(x1,y) app(filter2_0(),y) -> filter2_1(y) app(filter2_1(x1),y) -> filter2_2(x1,y) app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) app(map_0(),y) -> map_1(y) app(map_1(x1),y) -> map_2(x1,y) app(s_0(),y) -> s_1(y) f_3(|0|_0(),|1|_0(),x) -> f_3(s_1(x),x,x) f_3(x,y,s_1(z)) -> s_1(f_3(|0|_0(),|1|_0(),z)) map_2(|fun|,nil_0()) -> nil_0() map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs)) filter_2(|fun|,nil_0()) -> nil_0() filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs) filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs)) filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs) -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: app#(f_2(x1,x2),y) -> f_3#(x1,x2,y) p2: app#(filter_1(x1),y) -> filter_2#(x1,y) p3: app#(filter2_3(x1,x2,x3),y) -> filter2_4#(x1,x2,x3,y) p4: app#(map_1(x1),y) -> map_2#(x1,y) p5: f_3#(|0|_0(),|1|_0(),x) -> f_3#(s_1(x),x,x) p6: f_3#(x,y,s_1(z)) -> f_3#(|0|_0(),|1|_0(),z) p7: map_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x) p8: map_2#(|fun|,cons_2(x,xs)) -> map_2#(|fun|,xs) p9: filter_2#(|fun|,cons_2(x,xs)) -> filter2_4#(app(|fun|,x),|fun|,x,xs) p10: filter_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x) p11: filter2_4#(true_0(),|fun|,x,xs) -> filter_2#(|fun|,xs) p12: filter2_4#(false_0(),|fun|,x,xs) -> filter_2#(|fun|,xs) and R consists of: r1: app(cons_0(),y) -> cons_1(y) r2: app(cons_1(x1),y) -> cons_2(x1,y) r3: app(f_0(),y) -> f_1(y) r4: app(f_1(x1),y) -> f_2(x1,y) r5: app(f_2(x1,x2),y) -> f_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: app(filter2_0(),y) -> filter2_1(y) r9: app(filter2_1(x1),y) -> filter2_2(x1,y) r10: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r11: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r12: app(map_0(),y) -> map_1(y) r13: app(map_1(x1),y) -> map_2(x1,y) r14: app(s_0(),y) -> s_1(y) r15: f_3(|0|_0(),|1|_0(),x) -> f_3(s_1(x),x,x) r16: f_3(x,y,s_1(z)) -> s_1(f_3(|0|_0(),|1|_0(),z)) r17: map_2(|fun|,nil_0()) -> nil_0() r18: map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs)) r19: filter_2(|fun|,nil_0()) -> nil_0() r20: filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs) r21: filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs)) r22: filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs) The estimated dependency graph contains the following SCCs: {p2, p3, p4, p7, p8, p9, p10, p11, p12} {p5, p6} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: map_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x) p2: app#(map_1(x1),y) -> map_2#(x1,y) p3: map_2#(|fun|,cons_2(x,xs)) -> map_2#(|fun|,xs) p4: app#(filter2_3(x1,x2,x3),y) -> filter2_4#(x1,x2,x3,y) p5: filter2_4#(false_0(),|fun|,x,xs) -> filter_2#(|fun|,xs) p6: filter_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x) p7: app#(filter_1(x1),y) -> filter_2#(x1,y) p8: filter_2#(|fun|,cons_2(x,xs)) -> filter2_4#(app(|fun|,x),|fun|,x,xs) p9: filter2_4#(true_0(),|fun|,x,xs) -> filter_2#(|fun|,xs) and R consists of: r1: app(cons_0(),y) -> cons_1(y) r2: app(cons_1(x1),y) -> cons_2(x1,y) r3: app(f_0(),y) -> f_1(y) r4: app(f_1(x1),y) -> f_2(x1,y) r5: app(f_2(x1,x2),y) -> f_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: app(filter2_0(),y) -> filter2_1(y) r9: app(filter2_1(x1),y) -> filter2_2(x1,y) r10: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r11: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r12: app(map_0(),y) -> map_1(y) r13: app(map_1(x1),y) -> map_2(x1,y) r14: app(s_0(),y) -> s_1(y) r15: f_3(|0|_0(),|1|_0(),x) -> f_3(s_1(x),x,x) r16: f_3(x,y,s_1(z)) -> s_1(f_3(|0|_0(),|1|_0(),z)) r17: map_2(|fun|,nil_0()) -> nil_0() r18: map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs)) r19: filter_2(|fun|,nil_0()) -> nil_0() r20: filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs) r21: filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs)) r22: filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs) The set of usable rules consists of (no rules) Take the reduction pair: generalized weighted path order (>=MG, >G) base order 1: trivial reduction triple (T x T, T x T, Φ) base order 2: lexicographic combination of reduction triples: 1. marked-algebra reduction triple (>=A, >=A!, >A!): matrix interpretation with standard point-wise order: carrier: N^1 order: standard order interpretations: map_2#_A(x1,x2) = x2 cons_2_A(x1,x2) = x1 + x2 + 2 app#_A(x1,x2) = x2 map_1_A(x1) = x1 filter2_3_A(x1,x2,x3) = x3 + 2 filter2_4#_A(x1,x2,x3,x4) = x4 false_0_A() = 1 filter_2#_A(x1,x2) = x2 filter_1_A(x1) = x1 app_A(x1,x2) = x2 + 1 true_0_A() = 1 map_2#!_A(x1,x2) = x2 + 2 cons_2!_A(x1,x2) = x1 + x2 + 7 app#!_A(x1,x2) = x2 + 3 map_1!_A(x1) = 1 filter2_3!_A(x1,x2,x3) = 5 filter2_4#!_A(x1,x2,x3,x4) = x4 + 3 false_0!_A() = 0 filter_2#!_A(x1,x2) = x2 + 3 filter_1!_A(x1) = 0 app!_A(x1,x2) = 6 true_0!_A() = 7 2. marked-algebra reduction triple (>=A, >=A!, >A!): matrix interpretation with standard point-wise order: carrier: N^1 order: standard order interpretations: map_2#_A(x1,x2) = x1 + x2 cons_2_A(x1,x2) = x1 + x2 + 2 app#_A(x1,x2) = x1 + x2 map_1_A(x1) = x1 + 2 filter2_3_A(x1,x2,x3) = x1 + x2 + x3 + 4 filter2_4#_A(x1,x2,x3,x4) = x2 + x4 + 2 false_0_A() = 1 filter_2#_A(x1,x2) = x1 + x2 + 2 filter_1_A(x1) = x1 + 2 app_A(x1,x2) = x2 true_0_A() = 1 map_2#!_A(x1,x2) = x1 + x2 + 2 cons_2!_A(x1,x2) = x2 + 5 app#!_A(x1,x2) = x1 + x2 + 1 map_1!_A(x1) = 1 filter2_3!_A(x1,x2,x3) = x2 + 3 filter2_4#!_A(x1,x2,x3,x4) = x4 + 4 false_0!_A() = 11 filter_2#!_A(x1,x2) = x2 + 3 filter_1!_A(x1) = 11 app!_A(x1,x2) = x1 + 9 true_0!_A() = 11 partial status: pi(map_2#) = [] pi(cons_2) = [2] pi(app#) = [] pi(map_1) = [1] pi(filter2_3) = [] pi(filter2_4#) = [] pi(false_0) = [] pi(filter_2#) = [] pi(filter_1) = [1] pi(app) = [1, 2] pi(true_0) = [] The following rules are removed: p1, p2, p3, p4, p5, p6, p8, p9 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: app#(filter_1(x1),y) -> filter_2#(x1,y) and R consists of: r1: app(cons_0(),y) -> cons_1(y) r2: app(cons_1(x1),y) -> cons_2(x1,y) r3: app(f_0(),y) -> f_1(y) r4: app(f_1(x1),y) -> f_2(x1,y) r5: app(f_2(x1,x2),y) -> f_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: app(filter2_0(),y) -> filter2_1(y) r9: app(filter2_1(x1),y) -> filter2_2(x1,y) r10: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r11: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r12: app(map_0(),y) -> map_1(y) r13: app(map_1(x1),y) -> map_2(x1,y) r14: app(s_0(),y) -> s_1(y) r15: f_3(|0|_0(),|1|_0(),x) -> f_3(s_1(x),x,x) r16: f_3(x,y,s_1(z)) -> s_1(f_3(|0|_0(),|1|_0(),z)) r17: map_2(|fun|,nil_0()) -> nil_0() r18: map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs)) r19: filter_2(|fun|,nil_0()) -> nil_0() r20: filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs) r21: filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs)) r22: filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs) The estimated dependency graph contains the following SCCs: (no SCCs) -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: f_3#(|0|_0(),|1|_0(),x) -> f_3#(s_1(x),x,x) p2: f_3#(x,y,s_1(z)) -> f_3#(|0|_0(),|1|_0(),z) and R consists of: r1: app(cons_0(),y) -> cons_1(y) r2: app(cons_1(x1),y) -> cons_2(x1,y) r3: app(f_0(),y) -> f_1(y) r4: app(f_1(x1),y) -> f_2(x1,y) r5: app(f_2(x1,x2),y) -> f_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: app(filter2_0(),y) -> filter2_1(y) r9: app(filter2_1(x1),y) -> filter2_2(x1,y) r10: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r11: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r12: app(map_0(),y) -> map_1(y) r13: app(map_1(x1),y) -> map_2(x1,y) r14: app(s_0(),y) -> s_1(y) r15: f_3(|0|_0(),|1|_0(),x) -> f_3(s_1(x),x,x) r16: f_3(x,y,s_1(z)) -> s_1(f_3(|0|_0(),|1|_0(),z)) r17: map_2(|fun|,nil_0()) -> nil_0() r18: map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs)) r19: filter_2(|fun|,nil_0()) -> nil_0() r20: filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs) r21: filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs)) r22: filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs) The set of usable rules consists of (no rules) Take the reduction pair: generalized weighted path order (>=MG, >G) base order 1: trivial reduction triple (T x T, T x T, Φ) base order 2: lexicographic combination of reduction triples: 1. marked-algebra reduction triple (>=A, >=A!, >A!): matrix interpretation with standard point-wise order: carrier: N^1 order: standard order interpretations: f_3#_A(x1,x2,x3) = x3 |0|_0_A() = 1 |1|_0_A() = 1 s_1_A(x1) = x1 + 2 f_3#!_A(x1,x2,x3) = x3 + 5 |0|_0!_A() = 2 |1|_0!_A() = 2 s_1!_A(x1) = 4 2. marked-algebra reduction triple (>=A, >=A!, >A!): matrix interpretation with standard point-wise order: carrier: N^1 order: standard order interpretations: f_3#_A(x1,x2,x3) = 0 |0|_0_A() = 3 |1|_0_A() = 1 s_1_A(x1) = 2 f_3#!_A(x1,x2,x3) = x1 + 5 |0|_0!_A() = 6 |1|_0!_A() = 0 s_1!_A(x1) = 7 partial status: pi(f_3#) = [] pi(|0|_0) = [] pi(|1|_0) = [] pi(s_1) = [1] The following rules are removed: p1, p2 Then no dependency pair remains.