YES We show the termination of the TRS R: app(app(minus(),x),|0|()) -> x app(app(minus(),app(s(),x)),app(s(),y)) -> app(app(minus(),x),y) app(double(),|0|()) -> |0|() app(double(),app(s(),x)) -> app(s(),app(s(),app(double(),x))) app(app(plus(),|0|()),y) -> y app(app(plus(),app(s(),x)),y) -> app(s(),app(app(plus(),x),y)) app(app(plus(),app(s(),x)),y) -> app(app(plus(),x),app(s(),y)) app(app(plus(),app(s(),x)),y) -> app(s(),app(app(plus(),app(app(minus(),x),y)),app(double(),y))) 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(cons_0(),y) -> cons_1(y) app(cons_1(x1),y) -> cons_2(x1,y) app(double_0(),y) -> double_1(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(minus_0(),y) -> minus_1(y) app(minus_1(x1),y) -> minus_2(x1,y) app(plus_0(),y) -> plus_1(y) app(plus_1(x1),y) -> plus_2(x1,y) app(s_0(),y) -> s_1(y) minus_2(x,|0|_0()) -> x minus_2(s_1(x),s_1(y)) -> minus_2(x,y) double_1(|0|_0()) -> |0|_0() double_1(s_1(x)) -> s_1(s_1(double_1(x))) plus_2(|0|_0(),y) -> y plus_2(s_1(x),y) -> s_1(plus_2(x,y)) plus_2(s_1(x),y) -> plus_2(x,s_1(y)) plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) 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#(double_0(),y) -> double_1#(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: app#(minus_1(x1),y) -> minus_2#(x1,y) p6: app#(plus_1(x1),y) -> plus_2#(x1,y) p7: minus_2#(s_1(x),s_1(y)) -> minus_2#(x,y) p8: double_1#(s_1(x)) -> double_1#(x) p9: plus_2#(s_1(x),y) -> plus_2#(x,y) p10: plus_2#(s_1(x),y) -> plus_2#(x,s_1(y)) p11: plus_2#(s_1(x),y) -> plus_2#(minus_2(x,y),double_1(y)) p12: plus_2#(s_1(x),y) -> minus_2#(x,y) p13: plus_2#(s_1(x),y) -> double_1#(y) p14: map_2#(f,cons_2(x,xs)) -> app#(f,x) p15: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs) p16: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs) p17: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p18: filter2_4#(true_0(),f,x,xs) -> filter_2#(f,xs) p19: filter2_4#(false_0(),f,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The estimated dependency graph contains the following SCCs: {p2, p3, p4, p14, p15, p16, p17, p18, p19} {p9, p10, p11} {p8} {p7} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: map_2#(f,cons_2(x,xs)) -> app#(f,x) p2: app#(map_1(x1),y) -> map_2#(x1,y) p3: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs) p4: app#(filter2_3(x1,x2,x3),y) -> filter2_4#(x1,x2,x3,y) p5: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs) p6: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p7: app#(filter_1(x1),y) -> filter_2#(x1,y) 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(cons_0(),y) -> cons_1(y) r2: app(cons_1(x1),y) -> cons_2(x1,y) r3: app(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r2, r6, r7, r12, r14, r16, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: map_2#_A(x1,x2) = max{7, x1 - 9} cons_2_A(x1,x2) = max{6, x1 - 38, x2 - 38} app#_A(x1,x2) = max{7, x1 - 9} map_1_A(x1) = max{7, x1 + 6} filter2_3_A(x1,x2,x3) = max{x1 + 17, x2 + 4, x3 + 10} filter2_4#_A(x1,x2,x3,x4) = max{7, x2 - 6} false_0_A = 1 filter_2#_A(x1,x2) = max{7, x1 - 6} filter_1_A(x1) = x1 + 8 app_A(x1,x2) = max{28, x1 - 18, x2 - 18} true_0_A = 5 cons_0_A = 1 cons_1_A(x1) = max{2, x1 - 19} filter2_0_A = 1 filter2_1_A(x1) = max{2, x1 - 19} filter2_2_A(x1,x2) = max{3, x1 - 38, x2 - 19} minus_0_A = 19 minus_1_A(x1) = max{20, x1 - 19} plus_0_A = 16 plus_1_A(x1) = max{17, x1 - 19} s_0_A = 17 s_1_A(x1) = max{22, x1 - 25} filter_2_A(x1,x2) = max{9, x1 - 40, x2 - 46} nil_0_A = 8 base order 2: precedence: app = cons_0 = filter2_1 > filter2_0 = filter_2 > map_1 = false_0 = filter_1 = nil_0 > map_2# = cons_2 = app# = filter2_4# = filter_2# = cons_1 = plus_1 > filter2_3 = true_0 = minus_1 = plus_0 = s_1 > filter2_2 = minus_0 = s_0 partial status: pi(map_2#) = [] pi(cons_2) = [] pi(app#) = [] pi(map_1) = [1] pi(filter2_3) = [1, 3] pi(filter2_4#) = [] pi(false_0) = [] pi(filter_2#) = [] pi(filter_1) = [1] pi(app) = [] pi(true_0) = [] pi(cons_0) = [] pi(cons_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] pi(s_0) = [] pi(s_1) = [] pi(filter_2) = [] pi(nil_0) = [] The following rules are removed: p4 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: map_2#(f,cons_2(x,xs)) -> app#(f,x) p2: app#(map_1(x1),y) -> map_2#(x1,y) p3: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs) p4: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs) p5: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p6: app#(filter_1(x1),y) -> filter_2#(x1,y) p7: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs) p8: filter2_4#(true_0(),f,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The estimated dependency graph contains the following SCCs: {p1, p2, p3, p4, p5, p6, p7, p8} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: map_2#(f,cons_2(x,xs)) -> app#(f,x) p2: app#(filter_1(x1),y) -> filter_2#(x1,y) p3: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs) p4: filter2_4#(true_0(),f,x,xs) -> filter_2#(f,xs) p5: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p6: app#(map_1(x1),y) -> map_2#(x1,y) p7: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs) p8: filter2_4#(false_0(),f,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r4, r6, r8, r10, r12, r14, r16, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: map_2#_A(x1,x2) = max{4, x1 + 3} cons_2_A(x1,x2) = max{6, x1 - 16, x2 - 16} app#_A(x1,x2) = x1 + 2 filter_1_A(x1) = x1 + 5 filter_2#_A(x1,x2) = x1 + 4 filter2_4#_A(x1,x2,x3,x4) = x2 + 4 app_A(x1,x2) = max{12, x1 - 14, x2 + 5} true_0_A = 1 map_1_A(x1) = max{6, x1 + 3} false_0_A = 4 cons_0_A = 13 cons_1_A(x1) = 4 filter_0_A = 1 filter2_0_A = 10 filter2_1_A(x1) = max{11, x1 - 1} filter2_2_A(x1,x2) = max{13, x1 + 1, x2 + 6} filter2_3_A(x1,x2,x3) = max{0, x1 - 36, x2 - 9} map_0_A = 13 minus_0_A = 9 minus_1_A(x1) = max{10, x1 - 15} plus_0_A = 7 plus_1_A(x1) = max{8, x1 - 1} s_0_A = 1 s_1_A(x1) = max{6, x1 - 11} filter_2_A(x1,x2) = max{15, x1 + 13, x2 - 7} nil_0_A = 0 base order 2: precedence: filter2_2 > app > cons_2 = cons_0 = filter_2 > filter_1 = map_1 = false_0 = cons_1 = filter2_1 = filter2_3 = minus_1 = plus_1 = nil_0 > filter_2# = filter2_4# = filter_0 = filter2_0 = map_0 = minus_0 = plus_0 = s_1 > app# = true_0 = s_0 > map_2# partial status: pi(map_2#) = [1] pi(cons_2) = [] pi(app#) = [1] pi(filter_1) = [1] pi(filter_2#) = [] pi(filter2_4#) = [] pi(app) = [] pi(true_0) = [] pi(map_1) = [1] pi(false_0) = [] pi(cons_0) = [] pi(cons_1) = [] pi(filter_0) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [2] pi(filter2_3) = [] pi(map_0) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] pi(s_0) = [] pi(s_1) = [] pi(filter_2) = [1] pi(nil_0) = [] The following rules are removed: p2 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: map_2#(f,cons_2(x,xs)) -> app#(f,x) p2: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs) p3: filter2_4#(true_0(),f,x,xs) -> filter_2#(f,xs) p4: filter_2#(f,cons_2(x,xs)) -> app#(f,x) p5: app#(map_1(x1),y) -> map_2#(x1,y) p6: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs) p7: filter2_4#(false_0(),f,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The estimated dependency graph contains the following SCCs: {p2, p3, p7} {p1, p5, p6} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs) p2: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs) p3: filter2_4#(true_0(),f,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r3, r4, r6, r12, r14, r16, r19, r20, r21, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: filter2_4#_A(x1,x2,x3,x4) = max{x3 + 11, x4 + 3} false_0_A = 1 filter_2#_A(x1,x2) = max{2, x2 - 1} cons_2_A(x1,x2) = max{15, x1 + 13, x2 + 11} app_A(x1,x2) = x2 + 11 true_0_A = 12 cons_0_A = 1 cons_1_A(x1) = max{10, x1} double_0_A = 1 double_1_A(x1) = max{2, x1 - 15} filter_0_A = 11 filter_1_A(x1) = max{10, x1} filter2_0_A = 1 filter2_1_A(x1) = max{6, x1 - 11} minus_0_A = 1 minus_1_A(x1) = max{6, x1} plus_0_A = 11 plus_1_A(x1) = max{10, x1} s_0_A = 1 s_1_A(x1) = max{0, x1 - 16} |0|_0_A = 0 plus_2_A(x1,x2) = max{x1 - 30, x2 + 13} filter_2_A(x1,x2) = max{13, x1 - 12, x2 - 16} nil_0_A = 0 base order 2: precedence: plus_2 = filter_2 > app > cons_2 = double_1 = filter_1 = plus_1 = nil_0 > filter2_4# = cons_1 = double_0 = filter_0 = minus_1 = plus_0 = s_1 = |0|_0 > filter_2# = cons_0 = filter2_1 = minus_0 = s_0 > false_0 = true_0 = filter2_0 partial status: pi(filter2_4#) = [] pi(false_0) = [] pi(filter_2#) = [] pi(cons_2) = [2] pi(app) = [2] pi(true_0) = [] pi(cons_0) = [] pi(cons_1) = [1] pi(double_0) = [] pi(double_1) = [] pi(filter_0) = [] pi(filter_1) = [1] pi(filter2_0) = [] pi(filter2_1) = [] pi(minus_0) = [] pi(minus_1) = [1] pi(plus_0) = [] pi(plus_1) = [1] pi(s_0) = [] pi(s_1) = [] pi(|0|_0) = [] pi(plus_2) = [2] pi(filter_2) = [] pi(nil_0) = [] The following rules are removed: p3 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs) p2: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The estimated dependency graph contains the following SCCs: {p1, p2} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs) p2: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r4, r6, r7, r8, r10, r12, r14 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: filter2_4#_A(x1,x2,x3,x4) = max{x3 + 3, x4 + 21} false_0_A = 1 filter_2#_A(x1,x2) = x2 + 20 cons_2_A(x1,x2) = max{13, x1 - 16, x2 + 5} app_A(x1,x2) = max{15, x1 - 7, x2 - 7} cons_0_A = 5 cons_1_A(x1) = max{6, x1 - 9} filter_0_A = 1 filter_1_A(x1) = max{2, x1 - 8} filter2_0_A = 6 filter2_1_A(x1) = max{1, x1 - 8} filter2_2_A(x1,x2) = max{2, x1 - 16, x2 - 8} filter2_3_A(x1,x2,x3) = max{3, x1 - 24, x2 - 16, x3 - 32} map_0_A = 5 map_1_A(x1) = max{6, x1 - 8} minus_0_A = 5 minus_1_A(x1) = max{6, x1 - 7} plus_0_A = 1 plus_1_A(x1) = max{6, x1 - 8} base order 2: precedence: filter2_4# > filter_2# = app = filter_0 = filter2_0 > false_0 = cons_2 = filter_1 = map_1 = minus_1 = plus_1 > cons_1 = filter2_3 = map_0 = minus_0 = plus_0 > cons_0 = filter2_2 > filter2_1 partial status: pi(filter2_4#) = [4] pi(false_0) = [] pi(filter_2#) = [] pi(cons_2) = [2] pi(app) = [] pi(cons_0) = [] pi(cons_1) = [] pi(filter_0) = [] pi(filter_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(filter2_3) = [] pi(map_0) = [] pi(map_1) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] The following rules are removed: p2 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: filter2_4#(false_0(),f,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,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: map_2#(f,cons_2(x,xs)) -> app#(f,x) p2: app#(map_1(x1),y) -> map_2#(x1,y) p3: map_2#(f,cons_2(x,xs)) -> map_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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r2, r6, r7, r8, r10, r12, r14, r16, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: map_2#_A(x1,x2) = x1 + 9 cons_2_A(x1,x2) = max{4, x1 - 30, x2 - 30} app#_A(x1,x2) = x1 + 8 map_1_A(x1) = max{11, x1 + 10} app_A(x1,x2) = max{x1 - 12, x2 + 11} cons_0_A = 10 cons_1_A(x1) = max{11, x1 - 1} filter2_0_A = 13 filter2_1_A(x1) = max{8, x1 - 1} filter2_2_A(x1,x2) = max{9, x1 - 14, x2 - 1} filter2_3_A(x1,x2,x3) = max{10, x1 - 27, x2 - 14, x3 - 1} map_0_A = 1 minus_0_A = 11 minus_1_A(x1) = max{1, x1 - 13} plus_0_A = 1 plus_1_A(x1) = max{10, x1 - 1} s_0_A = 7 s_1_A(x1) = max{8, x1 - 11} filter_2_A(x1,x2) = max{5, x1 - 53, x2 - 38} nil_0_A = 0 base order 2: precedence: filter_2 = nil_0 > app > app# = map_1 = filter2_2 = filter2_3 > cons_2 = filter2_1 = map_0 = plus_1 > map_2# = cons_1 = filter2_0 = minus_1 = plus_0 = s_1 > cons_0 = minus_0 = s_0 partial status: pi(map_2#) = [1] pi(cons_2) = [] pi(app#) = [1] pi(map_1) = [1] pi(app) = [2] pi(cons_0) = [] pi(cons_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(filter2_3) = [] pi(map_0) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] pi(s_0) = [] pi(s_1) = [] pi(filter_2) = [] pi(nil_0) = [] The following rules are removed: p1 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: app#(map_1(x1),y) -> map_2#(x1,y) p2: map_2#(f,cons_2(x,xs)) -> map_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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The estimated dependency graph contains the following SCCs: {p2} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: map_2#(f,cons_2(x,xs)) -> map_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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r4, r6, r10, r12, r14, r16, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: map_2#_A(x1,x2) = max{x1 + 14, x2 + 23} cons_2_A(x1,x2) = max{12, x1 - 9, x2 + 1} app_A(x1,x2) = max{7, x2 - 9} cons_0_A = 8 cons_1_A(x1) = max{7, x1 - 9} filter_0_A = 1 filter_1_A(x1) = max{5, x1 - 9} filter2_0_A = 1 filter2_1_A(x1) = max{7, x1 - 9} map_0_A = 1 map_1_A(x1) = max{7, x1 - 9} minus_0_A = 1 minus_1_A(x1) = max{2, x1 - 9} plus_0_A = 1 plus_1_A(x1) = max{7, x1 - 9} s_0_A = 1 s_1_A(x1) = max{4, x1 - 11} filter_2_A(x1,x2) = max{6, x1 - 11, x2 - 11} nil_0_A = 0 base order 2: precedence: filter_2 > map_2# = cons_0 = map_0 = plus_0 = nil_0 > cons_2 > app > cons_1 = filter_1 = filter2_1 = map_1 = minus_1 = plus_1 = s_1 > filter_0 = filter2_0 = minus_0 = s_0 partial status: pi(map_2#) = [2] pi(cons_2) = [2] pi(app) = [] pi(cons_0) = [] pi(cons_1) = [] pi(filter_0) = [] pi(filter_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(map_0) = [] pi(map_1) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] pi(s_0) = [] pi(s_1) = [] pi(filter_2) = [] pi(nil_0) = [] The following rules are removed: p1 Then no dependency pair remains. -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: plus_2#(s_1(x),y) -> plus_2#(minus_2(x,y),double_1(y)) p2: plus_2#(s_1(x),y) -> plus_2#(x,s_1(y)) p3: plus_2#(s_1(x),y) -> plus_2#(x,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r2, r4, r6, r7, r8, r10, r12, r14, r17, r18 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: plus_2#_A(x1,x2) = max{1, x1 - 15} s_1_A(x1) = max{30, x1 + 17} minus_2_A(x1,x2) = max{14, x1} double_1_A(x1) = max{5, x1 - 35} app_A(x1,x2) = max{8, x1, x2 - 5} cons_0_A = 0 cons_1_A(x1) = max{0, x1 - 6} cons_2_A(x1,x2) = max{2, x2 - 8} filter_0_A = 1 filter_1_A(x1) = max{0, x1 - 6} filter2_0_A = 0 filter2_1_A(x1) = max{0, x1 - 6} filter2_2_A(x1,x2) = max{0, x1 - 23, x2 - 6} filter2_3_A(x1,x2,x3) = max{0, x1 - 23, x2 - 6, x3 - 5} map_0_A = 0 map_1_A(x1) = max{0, x1 - 6} minus_0_A = 2 minus_1_A(x1) = 1 plus_0_A = 0 plus_1_A(x1) = max{0, x1 - 35} |0|_0_A = 0 base order 2: precedence: s_1 = filter2_0 = minus_0 = plus_0 > minus_2 > minus_1 > app > plus_2# = double_1 = plus_1 > map_1 = |0|_0 > map_0 > cons_2 = filter_1 = filter2_3 > cons_1 = filter_0 = filter2_2 > cons_0 = filter2_1 partial status: pi(plus_2#) = [] pi(s_1) = [1] pi(minus_2) = [1] pi(double_1) = [] pi(app) = [1] pi(cons_0) = [] pi(cons_1) = [] pi(cons_2) = [] pi(filter_0) = [] pi(filter_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(filter2_3) = [] pi(map_0) = [] pi(map_1) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] pi(|0|_0) = [] The following rules are removed: p2 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: plus_2#(s_1(x),y) -> plus_2#(minus_2(x,y),double_1(y)) p2: plus_2#(s_1(x),y) -> plus_2#(x,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The estimated dependency graph contains the following SCCs: {p1, p2} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: plus_2#(s_1(x),y) -> plus_2#(minus_2(x,y),double_1(y)) p2: plus_2#(s_1(x),y) -> plus_2#(x,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r2, r4, r6, r7, r8, r10, r12, r14, r17, r18, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: plus_2#_A(x1,x2) = max{1, x1 - 4} s_1_A(x1) = max{13, x1 + 7} minus_2_A(x1,x2) = x1 + 3 double_1_A(x1) = max{18, x1 + 12} app_A(x1,x2) = max{15, x1 - 17, x2 - 25} cons_1_A(x1) = max{3, x1 - 1} cons_2_A(x1,x2) = max{4, x1 - 19, x2 - 26} filter_0_A = 13 filter_1_A(x1) = max{14, x1 - 26} filter2_0_A = 1 filter2_1_A(x1) = max{2, x1 - 26} filter2_2_A(x1,x2) = max{3, x1 - 44, x2 - 26} filter2_3_A(x1,x2,x3) = max{14, x1 - 62, x2 - 44, x3 - 26} map_0_A = 13 map_1_A(x1) = max{14, x1 - 26} minus_0_A = 16 minus_1_A(x1) = max{15, x1 - 26} plus_0_A = 16 plus_1_A(x1) = max{0, x1 - 26} |0|_0_A = 19 filter_2_A(x1,x2) = max{40, x1 - 2, x2 - 5} nil_0_A = 4 base order 2: precedence: double_1 > s_1 > plus_2# > minus_2 = filter_0 = |0|_0 = filter_2 = nil_0 > app > cons_1 = cons_2 = filter_1 = filter2_2 = filter2_3 = map_1 = minus_1 = plus_1 > filter2_1 = map_0 = minus_0 = plus_0 > filter2_0 partial status: pi(plus_2#) = [] pi(s_1) = [1] pi(minus_2) = [] pi(double_1) = [1] pi(app) = [] pi(cons_1) = [] pi(cons_2) = [] pi(filter_0) = [] pi(filter_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(filter2_3) = [] pi(map_0) = [] pi(map_1) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] pi(|0|_0) = [] pi(filter_2) = [] pi(nil_0) = [] The following rules are removed: p2 -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: plus_2#(s_1(x),y) -> plus_2#(minus_2(x,y),double_1(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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> 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: plus_2#(s_1(x),y) -> plus_2#(minus_2(x,y),double_1(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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r4, r6, r7, r8, r10, r12, r14, r17, r18, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: plus_2#_A(x1,x2) = max{1, x1 - 4} s_1_A(x1) = x1 + 21 minus_2_A(x1,x2) = max{3, x1} double_1_A(x1) = max{45, x1 - 43} app_A(x1,x2) = max{45, x1 - 12, x2 + 8} cons_0_A = 11 cons_1_A(x1) = max{6, x1 - 1} filter_0_A = 10 filter_1_A(x1) = max{11, x1 - 60} filter2_0_A = 8 filter2_1_A(x1) = max{9, x1 - 1} filter2_2_A(x1,x2) = max{10, x1 - 14, x2 - 1} filter2_3_A(x1,x2,x3) = max{11, x1 - 47, x2 - 59, x3 - 1} map_0_A = 9 map_1_A(x1) = max{10, x1 - 1} minus_0_A = 11 minus_1_A(x1) = max{10, x1 - 1} plus_0_A = 5 plus_1_A(x1) = max{6, x1 - 1} |0|_0_A = 0 filter_2_A(x1,x2) = max{46, x1 - 59, x2 - 41} nil_0_A = 0 base order 2: precedence: s_1 = cons_0 = minus_0 > minus_2 = map_1 > app = map_0 = filter_2 > double_1 = cons_1 = filter_1 = filter2_3 = minus_1 = plus_1 = nil_0 > plus_2# = filter_0 = filter2_2 = plus_0 = |0|_0 > filter2_1 > filter2_0 partial status: pi(plus_2#) = [] pi(s_1) = [1] pi(minus_2) = [1] pi(double_1) = [] pi(app) = [] pi(cons_0) = [] pi(cons_1) = [] pi(filter_0) = [] pi(filter_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(filter2_3) = [] pi(map_0) = [] pi(map_1) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] pi(|0|_0) = [] pi(filter_2) = [] pi(nil_0) = [] The following rules are removed: p1 Then no dependency pair remains. -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: double_1#(s_1(x)) -> double_1#(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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r2, r4, r6, r7, r8, r10, r12, r14 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: double_1#_A(x1) = x1 + 4 s_1_A(x1) = x1 + 4 app_A(x1,x2) = max{8, x1 - 9, x2 - 10} cons_0_A = 2 cons_1_A(x1) = max{3, x1 - 11} cons_2_A(x1,x2) = max{2, x2 - 10} filter_0_A = 8 filter_1_A(x1) = max{4, x1 - 10} filter2_0_A = 1 filter2_1_A(x1) = max{6, x1 - 11} filter2_2_A(x1,x2) = max{7, x1 - 21, x2 - 11} filter2_3_A(x1,x2,x3) = max{8, x1 - 30, x2 - 20, x3 - 10} map_0_A = 5 map_1_A(x1) = max{6, x1 - 11} minus_0_A = 3 minus_1_A(x1) = max{4, x1 - 11} plus_0_A = 5 plus_1_A(x1) = max{6, x1 - 11} base order 2: precedence: s_1 = cons_0 = map_0 > double_1# = app > map_1 = minus_1 = plus_1 > cons_2 = filter2_3 = minus_0 = plus_0 > cons_1 = filter_1 = filter2_2 > filter_0 = filter2_1 > filter2_0 partial status: pi(double_1#) = [1] pi(s_1) = [1] pi(app) = [] pi(cons_0) = [] pi(cons_1) = [] pi(cons_2) = [] pi(filter_0) = [] pi(filter_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(filter2_3) = [] pi(map_0) = [] pi(map_1) = [] pi(minus_0) = [] pi(minus_1) = [] pi(plus_0) = [] pi(plus_1) = [] The following rules are removed: p1 Then no dependency pair remains. -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: minus_2#(s_1(x),s_1(y)) -> minus_2#(x,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(double_0(),y) -> double_1(y) r4: app(filter_0(),y) -> filter_1(y) r5: app(filter_1(x1),y) -> filter_2(x1,y) r6: app(filter2_0(),y) -> filter2_1(y) r7: app(filter2_1(x1),y) -> filter2_2(x1,y) r8: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y) r9: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y) r10: app(map_0(),y) -> map_1(y) r11: app(map_1(x1),y) -> map_2(x1,y) r12: app(minus_0(),y) -> minus_1(y) r13: app(minus_1(x1),y) -> minus_2(x1,y) r14: app(plus_0(),y) -> plus_1(y) r15: app(plus_1(x1),y) -> plus_2(x1,y) r16: app(s_0(),y) -> s_1(y) r17: minus_2(x,|0|_0()) -> x r18: minus_2(s_1(x),s_1(y)) -> minus_2(x,y) r19: double_1(|0|_0()) -> |0|_0() r20: double_1(s_1(x)) -> s_1(s_1(double_1(x))) r21: plus_2(|0|_0(),y) -> y r22: plus_2(s_1(x),y) -> s_1(plus_2(x,y)) r23: plus_2(s_1(x),y) -> plus_2(x,s_1(y)) r24: plus_2(s_1(x),y) -> s_1(plus_2(minus_2(x,y),double_1(y))) r25: map_2(f,nil_0()) -> nil_0() r26: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs)) r27: filter_2(f,nil_0()) -> nil_0() r28: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs) r29: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs)) r30: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs) The set of usable rules consists of r1, r2, r4, r6, r8, r10, r12, r27 Take the reduction pair: generalized weighted path order (>=MG, >MG) base order 1: max/plus interpretation on natural numbers: minus_2#_A(x1,x2) = max{6, x1 + 1} s_1_A(x1) = x1 + 8 app_A(x1,x2) = max{10, x1 - 12, x2 + 2} cons_0_A = 2 cons_1_A(x1) = max{3, x1 - 8} cons_2_A(x1,x2) = max{4, x1 - 20, x2 - 9} filter_0_A = 6 filter_1_A(x1) = max{7, x1 - 11} filter2_0_A = 11 filter2_1_A(x1) = max{9, x1 - 2} filter2_2_A(x1,x2) = max{11, x1 - 1, x2 - 1} filter2_3_A(x1,x2,x3) = max{1, x1 - 14, x2 - 14, x3 - 1} map_0_A = 4 map_1_A(x1) = max{5, x1 - 1} minus_0_A = 2 minus_1_A(x1) = max{3, x1 - 1} filter_2_A(x1,x2) = max{8, x1 - 24, x2 - 8} nil_0_A = 7 base order 2: precedence: minus_2# = s_1 = cons_1 = filter2_2 = filter2_3 > app = cons_0 > cons_2 = filter2_1 = minus_1 = filter_2 > filter_1 = filter2_0 = map_1 = minus_0 = nil_0 > filter_0 = map_0 partial status: pi(minus_2#) = [1] pi(s_1) = [1] pi(app) = [] pi(cons_0) = [] pi(cons_1) = [] pi(cons_2) = [] pi(filter_0) = [] pi(filter_1) = [] pi(filter2_0) = [] pi(filter2_1) = [] pi(filter2_2) = [] pi(filter2_3) = [] pi(map_0) = [] pi(map_1) = [] pi(minus_0) = [] pi(minus_1) = [] pi(filter_2) = [] pi(nil_0) = [] The following rules are removed: p1 Then no dependency pair remains.