YES We show the termination of the TRS R: app(app(.(),|1|()),x) -> x app(app(.(),x),|1|()) -> x app(app(.(),app(i(),x)),x) -> |1|() app(app(.(),x),app(i(),x)) -> |1|() app(app(.(),app(i(),y)),app(app(.(),y),z)) -> z app(app(.(),y),app(app(.(),app(i(),y)),z)) -> z app(i(),|1|()) -> |1|() app(i(),app(i(),x)) -> x app(app(map(),f),nil()) -> nil() app(app(map(),f),app(app(cons(),x),xs)) -> app(app(cons(),app(f,x)),app(app(map(),f),xs)) app(app(filter(),f),nil()) -> nil() app(app(filter(),f),app(app(cons(),x),xs)) -> app(app(app(app(filter2(),app(f,x)),f),x),xs) app(app(app(app(filter2(),true()),f),x),xs) -> app(app(cons(),x),app(app(filter(),f),xs)) app(app(app(app(filter2(),false()),f),x),xs) -> app(app(filter(),f),xs) Instead we prove termination of the uncurried system: app(._0(),y) -> ._1(y) app(._1(x1),y) -> ._2(x1,y) app(cons_0(),y) -> cons_1(y) app(cons_1(x1),y) -> cons_2(x1,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(i_0(),y) -> i_1(y) app(map_0(),y) -> map_1(y) app(map_1(x1),y) -> map_2(x1,y) ._2(|1|_0(),x) -> x ._2(x,|1|_0()) -> x ._2(i_1(x),x) -> |1|_0() ._2(x,i_1(x)) -> |1|_0() ._2(i_1(y),._2(y,z)) -> z ._2(y,._2(i_1(y),z)) -> z i_1(|1|_0()) -> |1|_0() i_1(i_1(x)) -> x map_2(f,nil_0()) -> nil_0() map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) filter_2(f,nil_0()) -> nil_0() filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: app#(._1(x1),y) -> ._2#(x1,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#(i_0(),y) -> i_1#(y) p5: app#(map_1(x1),y) -> map_2#(x1,y) p6: map_2#(f,cons_2(x,xs)) -> app#(f,x) p7: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs) p8: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs) p9: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p10: filter2_4#(true_0(),f,x,xs) -> filter_2#(f,xs) p11: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs) and R consists of: r1: app(._0(),y) -> ._1(y) r2: app(._1(x1),y) -> ._2(x1,y) r3: app(cons_0(),y) -> cons_1(y) r4: app(cons_1(x1),y) -> cons_2(x1,y) r5: app(filter_0(),y) -> filter_1(y) r6: app(filter_1(x1),y) -> filter_2(x1,y) r7: app(filter2_0(),y) -> filter2_1(y) r8: app(filter2_1(x1),y) -> filter2_2(x1,y) r9: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r10: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r11: app(i_0(),y) -> i_1(y) r12: app(map_0(),y) -> map_1(y) r13: app(map_1(x1),y) -> map_2(x1,y) r14: ._2(|1|_0(),x) -> x r15: ._2(x,|1|_0()) -> x r16: ._2(i_1(x),x) -> |1|_0() r17: ._2(x,i_1(x)) -> |1|_0() r18: ._2(i_1(y),._2(y,z)) -> z r19: ._2(y,._2(i_1(y),z)) -> z r20: i_1(|1|_0()) -> |1|_0() r21: i_1(i_1(x)) -> x r22: map_2(f,nil_0()) -> nil_0() r23: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r24: filter_2(f,nil_0()) -> nil_0() r25: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r26: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r27: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The estimated dependency graph contains the following SCCs: {p2, p3, p5, p6, p7, p8, p9, p10, p11} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: app#(filter_1(x1),y) -> filter_2#(x1,y) p2: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p3: app#(map_1(x1),y) -> map_2#(x1,y) p4: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs) p5: map_2#(f,cons_2(x,xs)) -> app#(f,x) p6: app#(filter2_3(x1,x2,x3),y) -> filter2_4#(x1,x2,x3,y) p7: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs) p8: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs) p9: filter2_4#(true_0(),f,x,xs) -> filter_2#(f,xs) and R consists of: r1: app(._0(),y) -> ._1(y) r2: app(._1(x1),y) -> ._2(x1,y) r3: app(cons_0(),y) -> cons_1(y) r4: app(cons_1(x1),y) -> cons_2(x1,y) r5: app(filter_0(),y) -> filter_1(y) r6: app(filter_1(x1),y) -> filter_2(x1,y) r7: app(filter2_0(),y) -> filter2_1(y) r8: app(filter2_1(x1),y) -> filter2_2(x1,y) r9: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r10: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r11: app(i_0(),y) -> i_1(y) r12: app(map_0(),y) -> map_1(y) r13: app(map_1(x1),y) -> map_2(x1,y) r14: ._2(|1|_0(),x) -> x r15: ._2(x,|1|_0()) -> x r16: ._2(i_1(x),x) -> |1|_0() r17: ._2(x,i_1(x)) -> |1|_0() r18: ._2(i_1(y),._2(y,z)) -> z r19: ._2(y,._2(i_1(y),z)) -> z r20: i_1(|1|_0()) -> |1|_0() r21: i_1(i_1(x)) -> x r22: map_2(f,nil_0()) -> nil_0() r23: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r24: filter_2(f,nil_0()) -> nil_0() r25: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r26: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r27: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r11, r20, r21 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: app#_A(x1,x2) = 0 filter_1_A(x1) = x1 + 3 filter_2#_A(x1,x2) = 0 cons_2_A(x1,x2) = x1 + x2 + 7 map_1_A(x1) = x1 + 9 map_2#_A(x1,x2) = 0 filter2_3_A(x1,x2,x3) = x1 + x2 + x3 + 7 filter2_4#_A(x1,x2,x3,x4) = 0 false_0_A() = 1 app_A(x1,x2) = x1 + x2 + 1 true_0_A() = 1 i_0_A() = 1 i_1_A(x1) = x1 + 1 |1|_0_A() = 7 app#!_A(x1,x2) = x1 + x2 + 7 filter_1!_A(x1) = 1 filter_2#!_A(x1,x2) = x1 + x2 + 7 cons_2!_A(x1,x2) = 14 map_1!_A(x1) = 8 map_2#!_A(x1,x2) = x1 + x2 + 1 filter2_3!_A(x1,x2,x3) = x1 + x2 + 12 filter2_4#!_A(x1,x2,x3,x4) = x2 + x4 + 13 false_0!_A() = 8 app!_A(x1,x2) = x1 + x2 + 6 true_0!_A() = 15 i_0!_A() = 0 i_1!_A(x1) = 1 |1|_0!_A() = 0 2. marked-algebra reduction triple (>=A, >=A!, >A!): max/plus interpretation on natural numbers: app#_A(x1,x2) = max{1, x1 - 52} filter_1_A(x1) = x1 + 27 filter_2#_A(x1,x2) = max{1, x1 - 52} cons_2_A(x1,x2) = 0 map_1_A(x1) = max{28, x1 + 27} map_2#_A(x1,x2) = max{1, x1 - 25} filter2_3_A(x1,x2,x3) = max{x1 + 27, x2, x3 + 30} filter2_4#_A(x1,x2,x3,x4) = max{1, x2 - 52} false_0_A = 25 app_A(x1,x2) = max{25, x2 + 13} true_0_A = 25 i_0_A = 28 i_1_A(x1) = max{14, x1} |1|_0_A = 0 app#!_A(x1,x2) = 22 filter_1!_A(x1) = max{0, x1 - 70} filter_2#!_A(x1,x2) = 0 cons_2!_A(x1,x2) = max{21, x1 - 83, x2 - 57} map_1!_A(x1) = max{21, x1 - 31} map_2#!_A(x1,x2) = max{x1 + 24, x2 + 21} filter2_3!_A(x1,x2,x3) = max{18, x2 + 2, x3 - 85} filter2_4#!_A(x1,x2,x3,x4) = 0 false_0!_A = 21 app!_A(x1,x2) = max{20, x1 - 29, x2 + 17} true_0!_A = 22 i_0!_A = 22 i_1!_A(x1) = max{21, x1 - 1} |1|_0!_A = 0 partial status: pi(app#) = [] pi(filter_1) = [] pi(filter_2#) = [] pi(cons_2) = [1] pi(map_1) = [1] pi(map_2#) = [] pi(filter2_3) = [1] pi(filter2_4#) = [] pi(false_0) = [] pi(app) = [1, 2] pi(true_0) = [] pi(i_0) = [] pi(i_1) = [1] pi(|1|_0) = [] The following rules are removed: p1, p2, p3, p4, p5, p6, p7, p8, p9 Then no dependency pair remains.