YES
We show the termination of the TRS R:

  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(sum(),app(app(cons(),x),xs)) -> app(app(plus(),x),app(sum(),xs))
  app(size(),app(app(node(),x),xs)) -> app(s(),app(sum(),app(app(map(),size()),xs)))
  app(app(plus(),|0|()),x) -> |0|()
  app(app(plus(),app(s(),x)),y) -> app(s(),app(app(plus(),x),y))

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(map_0(),y) -> map_1(y)
  app(map_1(x1),y) -> map_2(x1,y)
  app(node_0(),y) -> node_1(y)
  app(node_1(x1),y) -> node_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)
  app(size_0(),y) -> size_1(y)
  app(sum_0(),y) -> sum_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))
  sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
  size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
  plus_2(|0|_0(),x) -> |0|_0()
  plus_2(s_1(x),y) -> s_1(plus_2(x,y))


-- SCC decomposition.

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

p1: app#(map_1(x1),y) -> map_2#(x1,y)
p2: app#(plus_1(x1),y) -> plus_2#(x1,y)
p3: app#(size_0(),y) -> size_1#(y)
p4: app#(sum_0(),y) -> sum_1#(y)
p5: map_2#(f,cons_2(x,xs)) -> app#(f,x)
p6: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs)
p7: sum_1#(cons_2(x,xs)) -> plus_2#(x,sum_1(xs))
p8: sum_1#(cons_2(x,xs)) -> sum_1#(xs)
p9: size_1#(node_2(x,xs)) -> sum_1#(map_2(size_0(),xs))
p10: size_1#(node_2(x,xs)) -> map_2#(size_0(),xs)
p11: 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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

The estimated dependency graph contains the following SCCs:

  {p1, p3, p5, p6, p10}
  {p8}
  {p11}


-- Reduction pair.

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)
p3: map_2#(f,cons_2(x,xs)) -> app#(f,x)
p4: app#(size_0(),y) -> size_1#(y)
p5: size_1#(node_2(x,xs)) -> map_2#(size_0(),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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

The set of usable rules consists of

  r16, r17

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      matrix interpretation with standard point-wise order:
      
        carrier: N^1
        order: standard order
        interpretations:
          app#_A(x1,x2) = x2 + 4
          map_1_A(x1) = 1
          map_2#_A(x1,x2) = x2 + 2
          cons_2_A(x1,x2) = x1 + x2 + 6
          size_0_A() = 2
          size_1#_A(x1) = x1 + 3
          node_2_A(x1,x2) = x2 + 12
          plus_2_A(x1,x2) = x1 + x2 + 3
          |0|_0_A() = 1
          s_1_A(x1) = x1 + 2
  
    base order 2:
  
      precedence:
      
        plus_2 > s_1 > app# > cons_2 = size_1# = |0|_0 > map_1 = node_2 > map_2# = size_0
      
  
    partial status:
  
      pi(app#) = [2]
      pi(map_1) = []
      pi(map_2#) = []
      pi(cons_2) = [1]
      pi(size_0) = []
      pi(size_1#) = [1]
      pi(node_2) = []
      pi(plus_2) = []
      pi(|0|_0) = []
      pi(s_1) = [1]

The following rules are removed:

  p1



-- SCC decomposition.

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

p1: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs)
p2: map_2#(f,cons_2(x,xs)) -> app#(f,x)
p3: app#(size_0(),y) -> size_1#(y)
p4: size_1#(node_2(x,xs)) -> map_2#(size_0(),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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

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: map_2#(f,cons_2(x,xs)) -> map_2#(f,xs)
p2: map_2#(f,cons_2(x,xs)) -> app#(f,x)
p3: app#(size_0(),y) -> size_1#(y)
p4: size_1#(node_2(x,xs)) -> map_2#(size_0(),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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

The set of usable rules consists of

  r1, r3, r5, r6, r7, r9, r16, r17

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      matrix interpretation with standard point-wise order:
      
        carrier: N^1
        order: standard order
        interpretations:
          map_2#_A(x1,x2) = x1 + x2 + 5
          cons_2_A(x1,x2) = x1 + x2 + 12
          app#_A(x1,x2) = x2 + 11
          size_0_A() = 1
          size_1#_A(x1) = x1 + 2
          node_2_A(x1,x2) = x2 + 7
          app_A(x1,x2) = x2 + 8
          cons_0_A() = 2
          cons_1_A(x1) = 1
          map_0_A() = 2
          map_1_A(x1) = 1
          node_0_A() = 1
          node_1_A(x1) = x1 + 2
          plus_0_A() = 2
          plus_1_A(x1) = 1
          s_0_A() = 1
          s_1_A(x1) = x1 + 2
          plus_2_A(x1,x2) = x1 + x2 + 9
          |0|_0_A() = 1
  
    base order 2:
  
      precedence:
      
        size_1# = plus_2 > map_2# = s_1 > node_2 > size_0 = app = cons_0 = map_0 = plus_0 = s_0 = |0|_0 > cons_2 = app# = map_1 = node_1 = plus_1 > cons_1 = node_0
      
  
    partial status:
  
      pi(map_2#) = [2]
      pi(cons_2) = [2]
      pi(app#) = []
      pi(size_0) = []
      pi(size_1#) = []
      pi(node_2) = []
      pi(app) = [2]
      pi(cons_0) = []
      pi(cons_1) = []
      pi(map_0) = []
      pi(map_1) = []
      pi(node_0) = []
      pi(node_1) = [1]
      pi(plus_0) = []
      pi(plus_1) = []
      pi(s_0) = []
      pi(s_1) = [1]
      pi(plus_2) = [1, 2]
      pi(|0|_0) = []

The following rules are removed:

  p1



-- 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#(size_0(),y) -> size_1#(y)
p3: size_1#(node_2(x,xs)) -> map_2#(size_0(),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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

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: map_2#(f,cons_2(x,xs)) -> app#(f,x)
p2: app#(size_0(),y) -> size_1#(y)
p3: size_1#(node_2(x,xs)) -> map_2#(size_0(),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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

The set of usable rules consists of

  r1, r3, r5, r6, r7, r9, r16, r17

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      matrix interpretation with standard point-wise order:
      
        carrier: N^1
        order: standard order
        interpretations:
          map_2#_A(x1,x2) = x1 + x2
          cons_2_A(x1,x2) = x1 + x2
          app#_A(x1,x2) = x2
          size_0_A() = 0
          size_1#_A(x1) = x1
          node_2_A(x1,x2) = x2
          app_A(x1,x2) = x2 + 4
          cons_0_A() = 2
          cons_1_A(x1) = x1 + 1
          map_0_A() = 1
          map_1_A(x1) = x1 + 3
          node_0_A() = 1
          node_1_A(x1) = x1 + 2
          plus_0_A() = 2
          plus_1_A(x1) = 1
          s_0_A() = 2
          s_1_A(x1) = x1 + 1
          plus_2_A(x1,x2) = x1 + x2 + 5
          |0|_0_A() = 1
  
    base order 2:
  
      precedence:
      
        plus_2 > cons_1 = plus_0 = s_1 > cons_2 = node_2 = app = cons_0 = node_1 = plus_1 = s_0 = |0|_0 > map_2# = map_1 = node_0 > app# = size_0 = map_0 > size_1#
      
  
    partial status:
  
      pi(map_2#) = [2]
      pi(cons_2) = [1, 2]
      pi(app#) = [2]
      pi(size_0) = []
      pi(size_1#) = [1]
      pi(node_2) = [2]
      pi(app) = [2]
      pi(cons_0) = []
      pi(cons_1) = [1]
      pi(map_0) = []
      pi(map_1) = [1]
      pi(node_0) = []
      pi(node_1) = [1]
      pi(plus_0) = []
      pi(plus_1) = []
      pi(s_0) = []
      pi(s_1) = [1]
      pi(plus_2) = []
      pi(|0|_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: size_1#(node_2(x,xs)) -> map_2#(size_0(),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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

The estimated dependency graph contains the following SCCs:

  (no SCCs)

-- Reduction pair.

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

p1: sum_1#(cons_2(x,xs)) -> sum_1#(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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

The set of usable rules consists of

  r1, r2, r3, r5, r6, r7, r8, r9, r16, r17

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      matrix interpretation with standard point-wise order:
      
        carrier: N^1
        order: standard order
        interpretations:
          sum_1#_A(x1) = x1
          cons_2_A(x1,x2) = x1 + x2 + 5
          app_A(x1,x2) = x1 + x2 + 6
          cons_0_A() = 1
          cons_1_A(x1) = x1 + 2
          map_0_A() = 1
          map_1_A(x1) = x1 + 2
          node_0_A() = 1
          node_1_A(x1) = x1 + 2
          node_2_A(x1,x2) = x2 + 7
          plus_0_A() = 1
          plus_1_A(x1) = x1 + 2
          plus_2_A(x1,x2) = x1 + x2 + 3
          s_0_A() = 1
          s_1_A(x1) = x1 + 2
          |0|_0_A() = 1
  
    base order 2:
  
      precedence:
      
        app > node_2 > node_1 > cons_2 = map_1 = node_0 > sum_1# = cons_1 = map_0 > cons_0 = plus_2 > plus_1 = s_1 = |0|_0 > plus_0 = s_0
      
  
    partial status:
  
      pi(sum_1#) = []
      pi(cons_2) = [2]
      pi(app) = [2]
      pi(cons_0) = []
      pi(cons_1) = [1]
      pi(map_0) = []
      pi(map_1) = [1]
      pi(node_0) = []
      pi(node_1) = [1]
      pi(node_2) = []
      pi(plus_0) = []
      pi(plus_1) = [1]
      pi(plus_2) = [1]
      pi(s_0) = []
      pi(s_1) = []
      pi(|0|_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#(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(map_0(),y) -> map_1(y)
r4: app(map_1(x1),y) -> map_2(x1,y)
r5: app(node_0(),y) -> node_1(y)
r6: app(node_1(x1),y) -> node_2(x1,y)
r7: app(plus_0(),y) -> plus_1(y)
r8: app(plus_1(x1),y) -> plus_2(x1,y)
r9: app(s_0(),y) -> s_1(y)
r10: app(size_0(),y) -> size_1(y)
r11: app(sum_0(),y) -> sum_1(y)
r12: map_2(f,nil_0()) -> nil_0()
r13: map_2(f,cons_2(x,xs)) -> cons_2(app(f,x),map_2(f,xs))
r14: sum_1(cons_2(x,xs)) -> plus_2(x,sum_1(xs))
r15: size_1(node_2(x,xs)) -> s_1(sum_1(map_2(size_0(),xs)))
r16: plus_2(|0|_0(),x) -> |0|_0()
r17: plus_2(s_1(x),y) -> s_1(plus_2(x,y))

The set of usable rules consists of

  r1, r5, r6, r7, r9, r16, r17

Take the reduction pair:

  generalized weighted path order (>=MG, >MG)
  
    base order 1:
  
      matrix interpretation with standard point-wise order:
      
        carrier: N^1
        order: standard order
        interpretations:
          plus_2#_A(x1,x2) = x1 + x2 + 3
          s_1_A(x1) = x1 + 2
          app_A(x1,x2) = x2 + 11
          cons_0_A() = 2
          cons_1_A(x1) = 1
          node_0_A() = 2
          node_1_A(x1) = 1
          node_2_A(x1,x2) = x2 + 10
          plus_0_A() = 11
          plus_1_A(x1) = 10
          s_0_A() = 1
          plus_2_A(x1,x2) = x1 + x2 + 9
          |0|_0_A() = 1
  
    base order 2:
  
      precedence:
      
        plus_2 > app = plus_0 > plus_1 > plus_2# = node_0 = node_2 > s_1 = node_1 = |0|_0 > s_0 > cons_1 > cons_0
      
  
    partial status:
  
      pi(plus_2#) = [1, 2]
      pi(s_1) = []
      pi(app) = [2]
      pi(cons_0) = []
      pi(cons_1) = []
      pi(node_0) = []
      pi(node_1) = []
      pi(node_2) = [2]
      pi(plus_0) = []
      pi(plus_1) = []
      pi(s_0) = []
      pi(plus_2) = []
      pi(|0|_0) = []

The following rules are removed:

  p1

Then no dependency pair remains.