We consider the system AotoYamada_05__022. Alphabet: cons : [b * c] --> c leaf : [a] --> b mapt : [a -> a * b] --> b maptlist : [a -> a * c] --> c nil : [] --> c node : [c] --> b Rules: mapt(f, leaf(x)) => leaf(f x) mapt(f, node(x)) => node(maptlist(f, x)) maptlist(f, nil) => nil maptlist(f, cons(x, y)) => cons(mapt(f, x), maptlist(f, y)) This AFS is converted to an AFSM simply by replacing all free variables by meta-variables (with arity 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 [Kop13]). We thus obtain the following dependency pair problem (P_0, R_0, static, formative): Dependency Pairs P_0: 0] mapt#(F, node(X)) =#> maptlist#(F, X) 1] maptlist#(F, cons(X, Y)) =#> mapt#(F, X) 2] maptlist#(F, cons(X, Y)) =#> maptlist#(F, Y) Rules R_0: mapt(F, leaf(X)) => leaf(F X) mapt(F, node(X)) => node(maptlist(F, X)) maptlist(F, nil) => nil maptlist(F, cons(X, Y)) => cons(mapt(F, X), maptlist(F, Y)) Thus, the original system is terminating if (P_0, R_0, static, formative) is finite. We consider the dependency pair problem (P_0, R_0, static, formative). We will use the reduction pair processor [Kop12, Thm. 7.16]. It suffices to find a standard reduction pair [Kop12, Def. 6.69]. Thus, we must orient: mapt#(F, node(X)) >? maptlist#(F, X) maptlist#(F, cons(X, Y)) >? mapt#(F, X) maptlist#(F, cons(X, Y)) >? maptlist#(F, Y) mapt(F, leaf(X)) >= leaf(F X) mapt(F, node(X)) >= node(maptlist(F, X)) maptlist(F, nil) >= nil maptlist(F, cons(X, Y)) >= cons(mapt(F, X), maptlist(F, Y)) We orient these requirements with a polynomial interpretation in the natural numbers. The following interpretation satisfies the requirements: cons = \y0y1.2 + y0 + 2y1 leaf = \y0.0 mapt = \G0y1.2 + 2y1 + 2y1G0(y1) mapt# = \G0y1.2y1 maptlist = \G0y1.2y1 + 2y1G0(y1) maptlist# = \G0y1.2y1 nil = 0 node = \y0.2y0 Using this interpretation, the requirements translate to: [[mapt#(_F0, node(_x1))]] = 4x1 >= 2x1 = [[maptlist#(_F0, _x1)]] [[maptlist#(_F0, cons(_x1, _x2))]] = 4 + 2x1 + 4x2 > 2x1 = [[mapt#(_F0, _x1)]] [[maptlist#(_F0, cons(_x1, _x2))]] = 4 + 2x1 + 4x2 > 2x2 = [[maptlist#(_F0, _x2)]] [[mapt(_F0, leaf(_x1))]] = 2 >= 0 = [[leaf(_F0 _x1)]] [[mapt(_F0, node(_x1))]] = 2 + 4x1 + 4x1F0(2x1) >= 4x1 + 4x1F0(x1) = [[node(maptlist(_F0, _x1))]] [[maptlist(_F0, nil)]] = 0 >= 0 = [[nil]] [[maptlist(_F0, cons(_x1, _x2))]] = 4 + 2x1 + 4x2 + 2x1F0(2 + x1 + 2x2) + 4x2F0(2 + x1 + 2x2) + 4F0(2 + x1 + 2x2) >= 4 + 2x1 + 4x2 + 2x1F0(x1) + 4x2F0(x2) = [[cons(mapt(_F0, _x1), maptlist(_F0, _x2))]] By the observations in [Kop12, Sec. 6.6], this reduction pair suffices; we may thus replace the dependency pair problem (P_0, R_0, static, formative) by (P_1, R_0, static, formative), where P_1 consists of: mapt#(F, node(X)) =#> maptlist#(F, X) Thus, the original system is terminating if (P_1, R_0, static, formative) is finite. We consider the dependency pair problem (P_1, R_0, static, formative). We will use the reduction pair processor [Kop12, Thm. 7.16]. It suffices to find a standard reduction pair [Kop12, Def. 6.69]. Thus, we must orient: mapt#(F, node(X)) >? maptlist#(F, X) mapt(F, leaf(X)) >= leaf(F X) mapt(F, node(X)) >= node(maptlist(F, X)) maptlist(F, nil) >= nil maptlist(F, cons(X, Y)) >= cons(mapt(F, X), maptlist(F, Y)) We orient these requirements with a polynomial interpretation in the natural numbers. The following interpretation satisfies the requirements: cons = \y0y1.0 leaf = \y0.0 mapt = \G0y1.2 + 2G0(0) + 3G0(y1) mapt# = \G0y1.3 maptlist = \G0y1.2 maptlist# = \G0y1.0 nil = 0 node = \y0.0 Using this interpretation, the requirements translate to: [[mapt#(_F0, node(_x1))]] = 3 > 0 = [[maptlist#(_F0, _x1)]] [[mapt(_F0, leaf(_x1))]] = 2 + 5F0(0) >= 0 = [[leaf(_F0 _x1)]] [[mapt(_F0, node(_x1))]] = 2 + 5F0(0) >= 0 = [[node(maptlist(_F0, _x1))]] [[maptlist(_F0, nil)]] = 2 >= 0 = [[nil]] [[maptlist(_F0, cons(_x1, _x2))]] = 2 >= 0 = [[cons(mapt(_F0, _x1), maptlist(_F0, _x2))]] By the observations in [Kop12, Sec. 6.6], this reduction pair suffices; we may thus replace a dependency pair problem (P_1, R_0) by ({}, R_0). 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 +++ [Kop12] C. Kop. Higher Order Termination. PhD Thesis, 2012. [Kop13] C. Kop. Static Dependency Pairs with Accessibility. Unpublished manuscript, http://cl-informatik.uibk.ac.at/users/kop/static.pdf, 2013. [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.