We consider the system Applicative_AG01_innermost__#4.24. Alphabet: 0 : [] --> b cons : [b * c] --> c false : [] --> a filter : [b -> a * c] --> c filter2 : [a * b -> a * b * c] --> c int : [b * b] --> c intlist : [c] --> c map : [b -> b * c] --> c nil : [] --> c s : [b] --> b true : [] --> a Rules: intlist(nil) => nil intlist(cons(x, y)) => cons(s(x), intlist(y)) int(0, 0) => cons(0, nil) int(0, s(x)) => cons(0, int(s(0), s(x))) int(s(x), 0) => nil int(s(x), s(y)) => intlist(int(x, y)) map(f, nil) => nil map(f, cons(x, y)) => cons(f x, map(f, y)) filter(f, nil) => nil filter(f, cons(x, y)) => filter2(f x, f, x, y) filter2(true, f, x, y) => cons(x, filter(f, y)) filter2(false, f, x, y) => filter(f, y) This AFS is converted to an AFSM simply by replacing all free variables by meta-variables (with arity 0). We observe that the rules contain a first-order subset: intlist(nil) => nil intlist(cons(X, Y)) => cons(s(X), intlist(Y)) int(0, 0) => cons(0, nil) int(0, s(X)) => cons(0, int(s(0), s(X))) int(s(X), 0) => nil int(s(X), s(Y)) => intlist(int(X, Y)) Moreover, the system is orthogonal. Thus, by [Kop12, Thm. 7.55], we may omit all first-order dependency pairs from the dependency pair problem (DP(R), R) if this first-order part is terminating when seen as a many-sorted first-order TRS. According to nattprover, this system is indeed terminating: || Input TRS: || 1: intlist(nil()) -> nil() || 2: intlist(cons(PeRCenTX,PeRCenTY)) -> cons(s(PeRCenTX),intlist(PeRCenTY)) || 3: int(0(),0()) -> cons(0(),nil()) || 4: int(0(),s(PeRCenTX)) -> cons(0(),int(s(0()),s(PeRCenTX))) || 5: int(s(PeRCenTX),0()) -> nil() || 6: int(s(PeRCenTX),s(PeRCenTY)) -> intlist(int(PeRCenTX,PeRCenTY)) || Number of strict rules: 6 || Direct POLO(bPol) ... removes: 3 5 || s w: x1 || 0 w: 0 || nil w: 1 || intlist w: x1 || int w: x1 + x2 + 2 || cons w: x1 + x2 || Number of strict rules: 4 || Direct POLO(bPol) ... removes: 1 || s w: 2 * x1 || 0 w: 0 || nil w: 1 || intlist w: 2 * x1 || int w: x1 + x2 || cons w: x1 + x2 || Number of strict rules: 3 || Direct POLO(bPol) ... failed. || Uncurrying int || 2: intlist(cons(PeRCenTX,PeRCenTY)) -> cons(s(PeRCenTX),intlist(PeRCenTY)) || 4: int^1_0(s(PeRCenTX)) -> cons(0(),int^1_s(0(),s(PeRCenTX))) || 6: int^1_s(PeRCenTX,s(PeRCenTY)) -> intlist(int(PeRCenTX,PeRCenTY)) || 7: int(0(),_1) ->= int^1_0(_1) || 8: int(s(_1),_2) ->= int^1_s(_1,_2) || Number of strict rules: 3 || Direct POLO(bPol) ... removes: 8 || int^1_0 w: 2 * x1 + 1 || s w: 2 * x1 + 1 || 0 w: 0 || nil w: 0 || intlist w: 2 * x1 || int w: x1 + 2 * x2 + 1 || cons w: x1 + x2 + 1 || int^1_s w: 2 * x1 + 2 * x2 || Number of strict rules: 3 || Direct POLO(bPol) ... failed. || Dependency Pairs: || #1: #intlist(cons(PeRCenTX,PeRCenTY)) -> #intlist(PeRCenTY) || #2: #int^1_s(PeRCenTX,s(PeRCenTY)) -> #intlist(int(PeRCenTX,PeRCenTY)) || #3: #int^1_s(PeRCenTX,s(PeRCenTY)) -> #int(PeRCenTX,PeRCenTY) || #4: #int(0(),_1) ->? #int^1_0(_1) || #5: #int^1_0(s(PeRCenTX)) -> #int^1_s(0(),s(PeRCenTX)) || Number of SCCs: 2, DPs: 4 || SCC { #1 } || POLO(Sum)... succeeded. || int^1_0 w: 0 || #intlist w: x1 || s w: 0 || 0 w: 0 || nil w: 0 || intlist w: 0 || #int^1_0 w: 0 || int w: 0 || cons w: x2 + 1 || int^1_s w: 0 || #int^1_s w: 0 || #int w: 0 || USABLE RULES: { } || Removed DPs: #1 || Number of SCCs: 1, DPs: 3 || SCC { #3..5 } || POLO(Sum)... succeeded. || int^1_0 w: 0 || #intlist w: 0 || s w: x1 + 3 || 0 w: 1 || nil w: 0 || intlist w: 0 || #int^1_0 w: x1 + 2 || int w: 0 || cons w: 1 || int^1_s w: 0 || #int^1_s w: x1 + x2 || #int w: x1 + x2 + 2 || USABLE RULES: { } || Removed DPs: #3..5 || Number of SCCs: 0, DPs: 0 || We use the dependency pair framework as described in [Kop12, Ch. 6/7], with static dependency pairs (see [KusIsoSakBla09] and the adaptation for AFSMs and accessible arguments in [FuhKop19]). We thus obtain the following dependency pair problem (P_0, R_0, computable, formative): Dependency Pairs P_0: 0] map#(F, cons(X, Y)) =#> map#(F, Y) 1] filter#(F, cons(X, Y)) =#> filter2#(F X, F, X, Y) 2] filter2#(true, F, X, Y) =#> filter#(F, Y) 3] filter2#(false, F, X, Y) =#> filter#(F, Y) Rules R_0: intlist(nil) => nil intlist(cons(X, Y)) => cons(s(X), intlist(Y)) int(0, 0) => cons(0, nil) int(0, s(X)) => cons(0, int(s(0), s(X))) int(s(X), 0) => nil int(s(X), s(Y)) => intlist(int(X, Y)) map(F, nil) => nil map(F, cons(X, Y)) => cons(F X, map(F, Y)) filter(F, nil) => nil filter(F, cons(X, Y)) => filter2(F X, F, X, Y) filter2(true, F, X, Y) => cons(X, filter(F, Y)) filter2(false, F, X, Y) => filter(F, Y) Thus, the original system is terminating if (P_0, R_0, computable, formative) is finite. We consider the dependency pair problem (P_0, R_0, computable, formative). We place the elements of P in a dependency graph approximation G (see e.g. [Kop12, Thm. 7.27, 7.29], as follows: * 0 : 0 * 1 : 2, 3 * 2 : 1 * 3 : 1 This graph has the following strongly connected components: P_1: map#(F, cons(X, Y)) =#> map#(F, Y) P_2: filter#(F, cons(X, Y)) =#> filter2#(F X, F, X, Y) filter2#(true, F, X, Y) =#> filter#(F, Y) filter2#(false, F, X, Y) =#> filter#(F, Y) By [Kop12, Thm. 7.31], we may replace any dependency pair problem (P_0, R_0, m, f) by (P_1, R_0, m, f) and (P_2, R_0, m, f). Thus, the original system is terminating if each of (P_1, R_0, computable, formative) and (P_2, R_0, computable, formative) is finite. We consider the dependency pair problem (P_2, R_0, computable, formative). We apply the subterm criterion with the following projection function: nu(filter2#) = 4 nu(filter#) = 2 Thus, we can orient the dependency pairs as follows: nu(filter#(F, cons(X, Y))) = cons(X, Y) |> Y = nu(filter2#(F X, F, X, Y)) nu(filter2#(true, F, X, Y)) = Y = Y = nu(filter#(F, Y)) nu(filter2#(false, F, X, Y)) = Y = Y = nu(filter#(F, Y)) By [FuhKop19, Thm. 61], we may replace a dependency pair problem (P_2, R_0, computable, f) by (P_3, R_0, computable, f), where P_3 contains: filter2#(true, F, X, Y) =#> filter#(F, Y) filter2#(false, F, X, Y) =#> filter#(F, Y) Thus, the original system is terminating if each of (P_1, R_0, computable, formative) and (P_3, R_0, computable, formative) is finite. We consider the dependency pair problem (P_3, R_0, computable, formative). We place the elements of P in a dependency graph approximation G (see e.g. [Kop12, Thm. 7.27, 7.29], as follows: * 0 : * 1 : This graph has no strongly connected components. By [Kop12, Thm. 7.31], this implies finiteness of the dependency pair problem. Thus, the original system is terminating if (P_1, R_0, computable, formative) is finite. We consider the dependency pair problem (P_1, R_0, computable, formative). We apply the subterm criterion with the following projection function: nu(map#) = 2 Thus, we can orient the dependency pairs as follows: nu(map#(F, cons(X, Y))) = cons(X, Y) |> Y = nu(map#(F, Y)) By [FuhKop19, Thm. 61], we may replace a dependency pair problem (P_1, R_0, computable, f) by ({}, R_0, computable, f). By the empty set processor [Kop12, Thm. 7.15] this problem may be immediately removed. As all dependency pair problems were succesfully simplified with sound (and complete) processors until nothing remained, we conclude termination. +++ Citations +++ [FuhKop19] C. Fuhs, and C. Kop. A static higher-order dependency pair framework. In Proceedings of ESOP 2019, 2019. [Kop12] C. Kop. Higher Order Termination. PhD Thesis, 2012. [KusIsoSakBla09] K. Kusakari, Y. Isogai, M. Sakai, and F. Blanqui. Static Dependency Pair Method Based On Strong Computability for Higher-Order Rewrite Systems. In volume 92(10) of IEICE Transactions on Information and Systems. 2007--2015, 2009.