YES We show the termination of the TRS R: app(app(app(consif(),true()),x),ys) -> app(app(cons(),x),ys) app(app(app(consif(),false()),x),ys) -> ys app(app(filter(),f),nil()) -> nil() app(app(filter(),f),app(app(cons(),x),xs)) -> app(app(app(consif(),app(f,x)),x),app(app(filter(),f),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(consif_0(),y) -> consif_1(y) app(consif_1(x1),y) -> consif_2(x1,y) app(consif_2(x1,x2),y) -> consif_3(x1,x2,y) app(filter_0(),y) -> filter_1(y) app(filter_1(x1),y) -> filter_2(x1,y) consif_3(true_0(),x,ys) -> cons_2(x,ys) consif_3(false_0(),x,ys) -> ys filter_2(f,nil_0()) -> nil_0() filter_2(f,cons_2(x,xs)) -> consif_3(app(f,x),x,filter_2(f,xs)) -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: app#(consif_2(x1,x2),y) -> consif_3#(x1,x2,y) p2: app#(filter_1(x1),y) -> filter_2#(x1,y) p3: filter_2#(f,cons_2(x,xs)) -> consif_3#(app(f,x),x,filter_2(f,xs)) p4: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p5: filter_2#(f,cons_2(x,xs)) -> filter_2#(f,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(consif_0(),y) -> consif_1(y) r4: app(consif_1(x1),y) -> consif_2(x1,y) r5: app(consif_2(x1,x2),y) -> consif_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: consif_3(true_0(),x,ys) -> cons_2(x,ys) r9: consif_3(false_0(),x,ys) -> ys r10: filter_2(f,nil_0()) -> nil_0() r11: filter_2(f,cons_2(x,xs)) -> consif_3(app(f,x),x,filter_2(f,xs)) The estimated dependency graph contains the following SCCs: {p2, p4, p5} -- 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)) -> filter_2#(f,xs) p3: filter_2#(f,cons_2(x,xs)) -> app#(f,x) and R consists of: r1: app(cons_0(),y) -> cons_1(y) r2: app(cons_1(x1),y) -> cons_2(x1,y) r3: app(consif_0(),y) -> consif_1(y) r4: app(consif_1(x1),y) -> consif_2(x1,y) r5: app(consif_2(x1,x2),y) -> consif_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: consif_3(true_0(),x,ys) -> cons_2(x,ys) r9: consif_3(false_0(),x,ys) -> ys r10: filter_2(f,nil_0()) -> nil_0() r11: filter_2(f,cons_2(x,xs)) -> consif_3(app(f,x),x,filter_2(f,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!): max/plus interpretation on natural numbers: app#_A(x1,x2) = max{0, x1 - 16, x2 - 4} filter_1_A(x1) = x1 + 15 filter_2#_A(x1,x2) = max{0, x1 - 16, x2 - 4} cons_2_A(x1,x2) = max{x1 + 3, x2} app#!_A(x1,x2) = max{3, x1 - 10, x2 - 3} filter_1!_A(x1) = max{1, x1 - 2} filter_2#!_A(x1,x2) = max{4, x1 - 2, x2 - 5} cons_2!_A(x1,x2) = max{2, x2 - 5} 2. marked-algebra reduction triple (>=A, >=A!, >A!): max/plus interpretation on natural numbers: app#_A(x1,x2) = max{0, x1 - 10, x2 - 4} filter_1_A(x1) = x1 + 9 filter_2#_A(x1,x2) = max{0, x1 - 10, x2 - 4} cons_2_A(x1,x2) = max{3, x1 + 2, x2} app#!_A(x1,x2) = max{5, x1 - 2, x2 - 27} filter_1!_A(x1) = max{2, x1 - 54} filter_2#!_A(x1,x2) = max{x1 + 6, x2 - 28} cons_2!_A(x1,x2) = max{3, x1 - 28, x2 - 27} partial status: pi(app#) = [] pi(filter_1) = [1] pi(filter_2#) = [] pi(cons_2) = [2] The following rules are removed: p1, p3 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: filter_2#(f,cons_2(x,xs)) -> filter_2#(f,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(consif_0(),y) -> consif_1(y) r4: app(consif_1(x1),y) -> consif_2(x1,y) r5: app(consif_2(x1,x2),y) -> consif_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: consif_3(true_0(),x,ys) -> cons_2(x,ys) r9: consif_3(false_0(),x,ys) -> ys r10: filter_2(f,nil_0()) -> nil_0() r11: filter_2(f,cons_2(x,xs)) -> consif_3(app(f,x),x,filter_2(f,xs)) The estimated dependency graph contains the following SCCs: {p1} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: filter_2#(f,cons_2(x,xs)) -> filter_2#(f,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(consif_0(),y) -> consif_1(y) r4: app(consif_1(x1),y) -> consif_2(x1,y) r5: app(consif_2(x1,x2),y) -> consif_3(x1,x2,y) r6: app(filter_0(),y) -> filter_1(y) r7: app(filter_1(x1),y) -> filter_2(x1,y) r8: consif_3(true_0(),x,ys) -> cons_2(x,ys) r9: consif_3(false_0(),x,ys) -> ys r10: filter_2(f,nil_0()) -> nil_0() r11: filter_2(f,cons_2(x,xs)) -> consif_3(app(f,x),x,filter_2(f,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!): max/plus interpretation on natural numbers: filter_2#_A(x1,x2) = x2 cons_2_A(x1,x2) = max{x1 - 3, x2 + 3} filter_2#!_A(x1,x2) = max{1, x2 - 2} cons_2!_A(x1,x2) = max{2, x1 - 10, x2 - 1} 2. marked-algebra reduction triple (>=A, >=A!, >A!): max/plus interpretation on natural numbers: filter_2#_A(x1,x2) = 0 cons_2_A(x1,x2) = max{4, x1 - 4, x2 - 6} filter_2#!_A(x1,x2) = max{1, x1 - 1, x2 - 5} cons_2!_A(x1,x2) = max{0, x1 - 11, x2 - 10} partial status: pi(filter_2#) = [2] pi(cons_2) = [2] The following rules are removed: p1 Then no dependency pair remains.