YES
We show the termination of the TRS R:

  app(app(|:|(),app(app(|:|(),app(app(|:|(),app(app(|:|(),C()),x)),y)),z)),u) -> app(app(|:|(),app(app(|:|(),x),z)),app(app(|:|(),app(app(|:|(),app(app(|:|(),x),y)),z)),u))
  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(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(|:|_0(),y) -> |:|_1(y)
  app(|:|_1(x1),y) -> |:|_2(x1,y)
  |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
  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#(filter_1(x1),y) -> filter_2#(x1,y)
p2: app#(filter2_3(x1,x2,x3),y) -> filter2_4#(x1,x2,x3,y)
p3: app#(map_1(x1),y) -> map_2#(x1,y)
p4: app#(|:|_1(x1),y) -> |:|_2#(x1,y)
p5: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p6: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,z)
p7: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)
p8: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,y),z)
p9: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,y)
p10: map_2#(f,cons_2(x,xs)) -> app#(f,x)
p11: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs)
p12: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs)
p13: filter_2#(f,cons_2(x,xs)) -> app#(f,x)
p14: filter2_4#(true_0(),f,x,xs) -> filter_2#(f,xs)
p15: 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The estimated dependency graph contains the following SCCs:

  {p1, p2, p3, p10, p11, p12, p13, p14, p15}
  {p5, p6, p7, p8, p9}


-- 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(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r2, r5, r6, r11, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        app#_A(x1,x2) = max{3, x1}
        filter_1_A(x1) = x1 + 6
        filter_2#_A(x1,x2) = x1 + 5
        cons_2_A(x1,x2) = max{2, x1 - 22, x2 - 22}
        map_1_A(x1) = x1 + 6
        map_2#_A(x1,x2) = x1 + 5
        filter2_3_A(x1,x2,x3) = max{x1 + 4, x2 + 5, x3 + 1}
        filter2_4#_A(x1,x2,x3,x4) = x2 + 5
        false_0_A = 6
        app_A(x1,x2) = max{9, x1 - 10, x2 - 10}
        true_0_A = 1
        cons_0_A = 9
        cons_1_A(x1) = max{1, x1 - 11}
        filter2_0_A = 1
        filter2_1_A(x1) = max{9, x1 - 10}
        filter2_2_A(x1,x2) = max{3, x1 - 20, x2 - 10}
        |:|_0_A = 6
        |:|_1_A(x1) = max{7, x1 - 10}
        filter_2_A(x1,x2) = max{7, x1 - 43, x2 - 26}
        nil_0_A = 0
  
    base order 2:
  
      precedence:
      
        filter_2 = nil_0 > app > filter_1 = filter2_3 = false_0 > map_1 = filter2_2 = |:|_1 > map_2# = filter2_1 = |:|_0 > app# = filter2_0 > filter_2# = cons_2 = filter2_4# > true_0 = cons_1 > cons_0
      
  
    partial status:
  
      pi(app#) = [1]
      pi(filter_1) = []
      pi(filter_2#) = []
      pi(cons_2) = []
      pi(map_1) = []
      pi(map_2#) = [1]
      pi(filter2_3) = []
      pi(filter2_4#) = []
      pi(false_0) = []
      pi(app) = []
      pi(true_0) = []
      pi(cons_0) = []
      pi(cons_1) = []
      pi(filter2_0) = []
      pi(filter2_1) = []
      pi(filter2_2) = []
      pi(|:|_0) = []
      pi(|:|_1) = []
      pi(filter_2) = []
      pi(nil_0) = []

The following rules are removed:

  p6



-- SCC decomposition.

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: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs)
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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: 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: app#(filter_1(x1),y) -> filter_2#(x1,y)
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)) -> app#(f,x)
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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r2, r5, r6, r7, r11, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        app#_A(x1,x2) = max{4, x1}
        filter_1_A(x1) = x1 + 9
        filter_2#_A(x1,x2) = x1 + 8
        cons_2_A(x1,x2) = max{3, x2 - 60}
        filter2_4#_A(x1,x2,x3,x4) = x2 + 8
        app_A(x1,x2) = max{12, x1 - 29, x2 - 29}
        true_0_A = 1
        map_1_A(x1) = max{12, x1 + 6}
        map_2#_A(x1,x2) = max{12, x1 + 5}
        false_0_A = 6
        cons_0_A = 1
        cons_1_A(x1) = max{2, x1 - 30}
        filter2_0_A = 7
        filter2_1_A(x1) = max{8, x1 - 30}
        filter2_2_A(x1,x2) = max{9, x1 - 60, x2 - 30}
        filter2_3_A(x1,x2,x3) = max{10, x1 - 89, x2 - 59, x3 - 29}
        |:|_0_A = 10
        |:|_1_A(x1) = max{11, x1 - 30}
        filter_2_A(x1,x2) = max{10, x1 - 149, x2 - 89}
        nil_0_A = 0
  
    base order 2:
  
      precedence:
      
        nil_0 > cons_0 = filter2_1 = filter_2 > app = filter2_0 > filter_1 = false_0 = filter2_3 = |:|_1 > filter_2# = filter2_4# = map_1 = filter2_2 = |:|_0 > cons_2 > app# = true_0 = cons_1 > map_2#
      
  
    partial status:
  
      pi(app#) = [1]
      pi(filter_1) = []
      pi(filter_2#) = []
      pi(cons_2) = []
      pi(filter2_4#) = []
      pi(app) = []
      pi(true_0) = []
      pi(map_1) = []
      pi(map_2#) = []
      pi(false_0) = []
      pi(cons_0) = []
      pi(cons_1) = []
      pi(filter2_0) = []
      pi(filter2_1) = []
      pi(filter2_2) = []
      pi(filter2_3) = []
      pi(|:|_0) = []
      pi(|:|_1) = []
      pi(filter_2) = []
      pi(nil_0) = []

The following rules are removed:

  p5



-- SCC decomposition.

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)) -> 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: map_2#(f,cons_2(x,xs)) -> app#(f,x)
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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The estimated dependency graph contains the following SCCs:

  {p6}
  {p1, p2, p3, p4, p7}


-- 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r3, r5, r6, r7, r9, r11, r16

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{14, x2}
        cons_2_A(x1,x2) = max{14, x1 + 2, x2 + 6}
        app_A(x1,x2) = max{3, x1 - 15, x2 - 27}
        cons_0_A = 1
        cons_1_A(x1) = max{2, x1 - 28}
        filter_0_A = 1
        filter_1_A(x1) = max{3, x1 - 27}
        filter2_0_A = 2
        filter2_1_A(x1) = max{3, x1 - 27}
        filter2_2_A(x1,x2) = max{2, x1 - 43, x2 - 28}
        filter2_3_A(x1,x2,x3) = max{3, x1 - 58, x2 - 43, x3 - 27}
        map_0_A = 2
        map_1_A(x1) = max{1, x1 - 28}
        |:|_0_A = 1
        |:|_1_A(x1) = max{2, x1 - 28}
        filter_2_A(x1,x2) = max{23, x1 - 14, x2 - 28}
        nil_0_A = 22
  
    base order 2:
  
      precedence:
      
        cons_2 > map_2# > filter_2 > app = nil_0 > cons_1 = filter_1 = filter2_3 = map_1 = |:|_1 > cons_0 = filter_0 = filter2_2 = map_0 = |:|_0 > filter2_1 > filter2_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(filter2_2) = []
      pi(filter2_3) = []
      pi(map_0) = []
      pi(map_1) = []
      pi(|:|_0) = []
      pi(|:|_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: app#(filter_1(x1),y) -> filter_2#(x1,y)
p2: filter_2#(f,cons_2(x,xs)) -> app#(f,x)
p3: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs)
p4: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs)
p5: 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r2, r5, r6, r7, r9, r11, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        app#_A(x1,x2) = max{1, x1 - 7}
        filter_1_A(x1) = x1 + 11
        filter_2#_A(x1,x2) = max{3, x1 - 6}
        cons_2_A(x1,x2) = max{13, x1 - 36, x2 - 36}
        filter2_4#_A(x1,x2,x3,x4) = max{3, x2 - 6}
        app_A(x1,x2) = max{35, x1 - 5, x2 - 5}
        false_0_A = 1
        true_0_A = 1
        cons_0_A = 1
        cons_1_A(x1) = max{4, x1 - 6}
        filter2_0_A = 3
        filter2_1_A(x1) = max{4, x1 - 6}
        filter2_2_A(x1,x2) = max{3, x1 - 12, x2 - 6}
        filter2_3_A(x1,x2,x3) = max{2, x1 - 17, x2 - 11, x3 - 5}
        map_0_A = 7
        map_1_A(x1) = max{1, x1 - 6}
        |:|_0_A = 3
        |:|_1_A(x1) = max{4, x1 - 6}
        filter_2_A(x1,x2) = max{12, x1 - 29, x2 - 14}
        nil_0_A = 0
  
    base order 2:
  
      precedence:
      
        app > filter_2# = filter2_4# > app# > cons_2 = filter2_3 > cons_1 = filter2_2 = map_1 = filter_2 = nil_0 > filter_1 = false_0 = true_0 = cons_0 = filter2_1 = map_0 = |:|_1 > filter2_0 = |:|_0
      
  
    partial status:
  
      pi(app#) = []
      pi(filter_1) = [1]
      pi(filter_2#) = []
      pi(cons_2) = []
      pi(filter2_4#) = []
      pi(app) = []
      pi(false_0) = []
      pi(true_0) = []
      pi(cons_0) = []
      pi(cons_1) = []
      pi(filter2_0) = []
      pi(filter2_1) = []
      pi(filter2_2) = []
      pi(filter2_3) = []
      pi(map_0) = []
      pi(map_1) = []
      pi(|:|_0) = []
      pi(|:|_1) = []
      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: app#(filter_1(x1),y) -> filter_2#(x1,y)
p2: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs)
p3: filter2_4#(false_0(),f,x,xs) -> filter_2#(f,xs)
p4: 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The estimated dependency graph contains the following SCCs:

  {p2, p3, p4}


-- Reduction pair.

Consider the dependency pair problem (P, R), where P consists of

p1: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs)
p2: filter2_4#(true_0(),f,x,xs) -> filter_2#(f,xs)
p3: 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r3, r5, r6, r7, r9, r11, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        filter_2#_A(x1,x2) = x2 + 82
        cons_2_A(x1,x2) = max{5, x1 - 40, x2 + 2}
        filter2_4#_A(x1,x2,x3,x4) = max{x3 + 41, x4 + 83}
        app_A(x1,x2) = max{39, x1 - 7, x2 - 7}
        true_0_A = 1
        false_0_A = 1
        cons_0_A = 3
        cons_1_A(x1) = max{4, x1 - 8}
        filter_0_A = 6
        filter_1_A(x1) = max{1, x1 - 33}
        filter2_0_A = 1
        filter2_1_A(x1) = max{2, x1 - 8}
        filter2_2_A(x1,x2) = max{3, x1 - 16, x2 - 8}
        filter2_3_A(x1,x2,x3) = max{4, x1 - 24, x2 - 16, x3 - 32}
        map_0_A = 6
        map_1_A(x1) = max{1, x1 - 7}
        |:|_0_A = 6
        |:|_1_A(x1) = max{0, x1 - 41}
        filter_2_A(x1,x2) = max{6, x1 - 40, x2 - 7}
        nil_0_A = 0
  
    base order 2:
  
      precedence:
      
        app > filter_2# = filter2_4# = |:|_1 = filter_2 > true_0 = false_0 = filter_1 = map_1 = |:|_0 = nil_0 > cons_2 = filter_0 = filter2_3 = map_0 > cons_1 = filter2_2 > cons_0 = filter2_1 > filter2_0
      
  
    partial status:
  
      pi(filter_2#) = []
      pi(cons_2) = [2]
      pi(filter2_4#) = [4]
      pi(app) = []
      pi(true_0) = []
      pi(false_0) = []
      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(|:|_0) = []
      pi(|:|_1) = []
      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: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs)
p2: 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: 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: filter_2#(f,cons_2(x,xs)) -> filter2_4#(app(f,x),f,x,xs)
p2: 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r6, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        filter_2#_A(x1,x2) = max{6, x2 + 1}
        cons_2_A(x1,x2) = max{27, x1 + 14, x2 + 18}
        filter2_4#_A(x1,x2,x3,x4) = max{x3 + 7, x4 + 7}
        app_A(x1,x2) = max{5, x1 - 34}
        true_0_A = 34
        filter2_1_A(x1) = x1 + 68
        filter2_2_A(x1,x2) = max{33, x1}
        filter_2_A(x1,x2) = max{7, x1 - 19, x2 - 17}
        nil_0_A = 0
  
    base order 2:
  
      precedence:
      
        filter_2 > app > cons_2 = nil_0 > filter_2# = filter2_4# > true_0 = filter2_2 > filter2_1
      
  
    partial status:
  
      pi(filter_2#) = [2]
      pi(cons_2) = [2]
      pi(filter2_4#) = []
      pi(app) = []
      pi(true_0) = []
      pi(filter2_1) = [1]
      pi(filter2_2) = [1]
      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: 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(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: 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: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p2: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,y)
p3: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,y),z)
p4: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)
p5: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,z)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r3, r5, r6, r7, r11, r13, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        |:|_2#_A(x1,x2) = x1 + 3
        |:|_2_A(x1,x2) = max{11, x1 + 6, x2}
        C_0_A = 1
        app_A(x1,x2) = max{4, x1 - 6, x2 - 29}
        filter_0_A = 5
        filter_1_A(x1) = max{4, x1 - 29}
        filter2_0_A = 1
        filter2_1_A(x1) = max{2, x1 - 30}
        filter2_2_A(x1,x2) = max{3, x1 - 37, x2 - 30}
        filter2_3_A(x1,x2,x3) = max{3, x1 - 44, x2 - 37}
        |:|_0_A = 14
        |:|_1_A(x1) = 7
        filter_2_A(x1,x2) = max{7, x1 - 28, x2 - 7}
        nil_0_A = 6
  
    base order 2:
  
      precedence:
      
        |:|_2# = |:|_2 = filter_2 > C_0 = app = filter2_0 = |:|_0 > filter_1 = filter2_2 = |:|_1 = nil_0 > filter_0 = filter2_1 = filter2_3
      
  
    partial status:
  
      pi(|:|_2#) = [1]
      pi(|:|_2) = [1, 2]
      pi(C_0) = []
      pi(app) = []
      pi(filter_0) = []
      pi(filter_1) = []
      pi(filter2_0) = []
      pi(filter2_1) = []
      pi(filter2_2) = []
      pi(filter2_3) = []
      pi(|:|_0) = []
      pi(|:|_1) = []
      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: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p2: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,y),z)
p3: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)
p4: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,z)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The estimated dependency graph contains the following SCCs:

  {p1, p2, p3, p4}


-- Reduction pair.

Consider the dependency pair problem (P, R), where P consists of

p1: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p2: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,z)
p3: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)
p4: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,y),z)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r2, r3, r5, r6, r9, r11, r13, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        |:|_2#_A(x1,x2) = x1 + 8
        |:|_2_A(x1,x2) = max{15, x1 + 8, x2}
        C_0_A = 1
        app_A(x1,x2) = max{x1 - 9, x2 + 14}
        cons_0_A = 10
        cons_1_A(x1) = max{6, x1 - 1}
        cons_2_A(x1,x2) = max{8, x1 - 13, x2 - 4}
        filter_0_A = 4
        filter_1_A(x1) = max{5, x1 - 28}
        filter2_0_A = 1
        filter2_1_A(x1) = max{2, x1 - 1}
        filter2_2_A(x1,x2) = max{1, x1 - 19}
        map_0_A = 1
        map_1_A(x1) = max{2, x1 - 1}
        |:|_0_A = 7
        |:|_1_A(x1) = max{8, x1 - 1}
        filter_2_A(x1,x2) = max{6, x1 - 38, x2 - 30}
        nil_0_A = 2
  
    base order 2:
  
      precedence:
      
        |:|_2# = |:|_2 > C_0 = app > cons_1 = filter2_1 = |:|_1 > cons_0 = cons_2 = filter2_0 = filter2_2 = |:|_0 > map_1 = filter_2 = nil_0 > filter_1 = map_0 > filter_0
      
  
    partial status:
  
      pi(|:|_2#) = [1]
      pi(|:|_2) = [1, 2]
      pi(C_0) = []
      pi(app) = [2]
      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(map_0) = []
      pi(map_1) = []
      pi(|:|_0) = []
      pi(|:|_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: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p2: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,z)
p3: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The estimated dependency graph contains the following SCCs:

  {p1, p2, p3}


-- Reduction pair.

Consider the dependency pair problem (P, R), where P consists of

p1: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p2: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)
p3: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(x,z)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r3, r5, r6, r11, r13, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        |:|_2#_A(x1,x2) = x1 + 4
        |:|_2_A(x1,x2) = max{10, x1 + 4, x2}
        C_0_A = 1
        app_A(x1,x2) = max{9, x1 - 8, x2 - 7}
        cons_0_A = 7
        cons_1_A(x1) = max{6, x1 - 35}
        filter_0_A = 1
        filter_1_A(x1) = max{2, x1 - 8}
        filter2_0_A = 7
        filter2_1_A(x1) = max{1, x1 - 8}
        filter2_2_A(x1,x2) = max{2, x1 - 17, x2 - 8}
        |:|_0_A = 10
        |:|_1_A(x1) = 9
        filter_2_A(x1,x2) = max{5, x1 - 17, x2 - 24}
        nil_0_A = 4
  
    base order 2:
  
      precedence:
      
        |:|_2# = |:|_2 > app > |:|_0 = filter_2 > C_0 = filter_1 = |:|_1 = nil_0 > cons_1 = filter_0 = filter2_0 = filter2_2 > cons_0 = filter2_1
      
  
    partial status:
  
      pi(|:|_2#) = [1]
      pi(|:|_2) = [1, 2]
      pi(C_0) = []
      pi(app) = []
      pi(cons_0) = []
      pi(cons_1) = []
      pi(filter_0) = []
      pi(filter_1) = []
      pi(filter2_0) = []
      pi(filter2_1) = []
      pi(filter2_2) = []
      pi(|:|_0) = []
      pi(|:|_1) = []
      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: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p2: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: 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: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
p2: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(|:|_2(x,y),z),u)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r2, r3, r5, r6, r7, r9, r11, r13, r16

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        |:|_2#_A(x1,x2) = max{38, x1 + 18, x2 + 9}
        |:|_2_A(x1,x2) = max{x1 + 3, x2}
        C_0_A = 11
        app_A(x1,x2) = max{43, x1 - 5, x2 - 1}
        cons_0_A = 1
        cons_1_A(x1) = max{2, x1 - 2}
        cons_2_A(x1,x2) = max{22, x1 - 9, x2 - 11}
        filter_0_A = 1
        filter_1_A(x1) = max{2, x1 - 1}
        filter2_0_A = 1
        filter2_1_A(x1) = max{2, x1 - 2}
        filter2_2_A(x1,x2) = max{3, x1 - 8, x2 - 2}
        filter2_3_A(x1,x2,x3) = max{4, x1 - 14, x2 - 8, x3 - 2}
        map_0_A = 4
        map_1_A(x1) = max{6, x1 - 9}
        |:|_0_A = 1
        |:|_1_A(x1) = max{2, x1 - 2}
        filter_2_A(x1,x2) = max{22, x1 - 26, x2 - 12}
        nil_0_A = 0
  
    base order 2:
  
      precedence:
      
        |:|_2# = |:|_2 > C_0 = app > |:|_1 > cons_2 = filter2_3 = map_1 = |:|_0 = filter_2 > cons_1 = filter_1 = filter2_2 = map_0 = nil_0 > cons_0 = filter_0 = filter2_1 > filter2_0
      
  
    partial status:
  
      pi(|:|_2#) = [1]
      pi(|:|_2) = [1, 2]
      pi(C_0) = []
      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(|:|_0) = []
      pi(|:|_1) = []
      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: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: 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: |:|_2#(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2#(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(filter_0(),y) -> filter_1(y)
r4: app(filter_1(x1),y) -> filter_2(x1,y)
r5: app(filter2_0(),y) -> filter2_1(y)
r6: app(filter2_1(x1),y) -> filter2_2(x1,y)
r7: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r8: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r9: app(map_0(),y) -> map_1(y)
r10: app(map_1(x1),y) -> map_2(x1,y)
r11: app(|:|_0(),y) -> |:|_1(y)
r12: app(|:|_1(x1),y) -> |:|_2(x1,y)
r13: |:|_2(|:|_2(|:|_2(|:|_2(C_0(),x),y),z),u) -> |:|_2(|:|_2(x,z),|:|_2(|:|_2(|:|_2(x,y),z),u))
r14: map_2(f,nil_0()) -> nil_0()
r15: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r16: filter_2(f,nil_0()) -> nil_0()
r17: filter_2(f,cons_2(x,xs)) -> filter2_4(app(f,x),f,x,xs)
r18: filter2_4(true_0(),f,x,xs) -> cons_2(x,filter_2(f,xs))
r19: filter2_4(false_0(),f,x,xs) -> filter_2(f,xs)

The set of usable rules consists of

  r1, r3, r5, r6, r7, r9, r11, r13

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      max/plus interpretation on natural numbers:
      
        |:|_2#_A(x1,x2) = max{x1 + 9, x2 + 3}
        |:|_2_A(x1,x2) = max{23, x1 + 4, x2}
        C_0_A = 1
        app_A(x1,x2) = max{7, x2 + 5}
        cons_0_A = 4
        cons_1_A(x1) = max{6, x1 + 3}
        filter_0_A = 4
        filter_1_A(x1) = 2
        filter2_0_A = 4
        filter2_1_A(x1) = 1
        filter2_2_A(x1,x2) = x2 + 3
        filter2_3_A(x1,x2,x3) = max{4, x3 - 1}
        map_0_A = 4
        map_1_A(x1) = 6
        |:|_0_A = 4
        |:|_1_A(x1) = max{7, x1 + 2}
  
    base order 2:
  
      precedence:
      
        |:|_2 = filter_1 > |:|_2# = app = filter_0 > C_0 = cons_1 = filter2_3 = map_1 = |:|_1 > cons_0 = filter2_2 = map_0 = |:|_0 > filter2_1 > filter2_0
      
  
    partial status:
  
      pi(|:|_2#) = [1]
      pi(|:|_2) = [1, 2]
      pi(C_0) = []
      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(|:|_0) = []
      pi(|:|_1) = [1]

The following rules are removed:

  p1

Then no dependency pair remains.