YES

We show the termination of the relative TRS R/S:

  R:
  le(|0|(),y) -> true()
  le(s(x),|0|()) -> false()
  le(s(x),s(y)) -> le(x,y)
  pred(s(x)) -> x
  minus(x,|0|()) -> x
  minus(x,s(y)) -> pred(minus(x,y))
  gcd(|0|(),y) -> y
  gcd(s(x),|0|()) -> s(x)
  gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
  if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
  if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))

  S:
  rand(x) -> x
  rand(x) -> rand(s(x))

-- SCC decomposition.

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

p1: le#(s(x),s(y)) -> le#(x,y)
p2: minus#(x,s(y)) -> pred#(minus(x,y))
p3: minus#(x,s(y)) -> minus#(x,y)
p4: gcd#(s(x),s(y)) -> if_gcd#(le(y,x),s(x),s(y))
p5: gcd#(s(x),s(y)) -> le#(y,x)
p6: if_gcd#(true(),s(x),s(y)) -> gcd#(minus(x,y),s(y))
p7: if_gcd#(true(),s(x),s(y)) -> minus#(x,y)
p8: if_gcd#(false(),s(x),s(y)) -> gcd#(minus(y,x),s(x))
p9: if_gcd#(false(),s(x),s(y)) -> minus#(y,x)

and R consists of:

r1: le(|0|(),y) -> true()
r2: le(s(x),|0|()) -> false()
r3: le(s(x),s(y)) -> le(x,y)
r4: pred(s(x)) -> x
r5: minus(x,|0|()) -> x
r6: minus(x,s(y)) -> pred(minus(x,y))
r7: gcd(|0|(),y) -> y
r8: gcd(s(x),|0|()) -> s(x)
r9: gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
r10: if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
r11: if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))
r12: rand(x) -> x
r13: rand(x) -> rand(s(x))

The estimated dependency graph contains the following SCCs:

  {p4, p6, p8}
  {p1}
  {p3}


-- Reduction pair.

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

p1: if_gcd#(false(),s(x),s(y)) -> gcd#(minus(y,x),s(x))
p2: gcd#(s(x),s(y)) -> if_gcd#(le(y,x),s(x),s(y))
p3: if_gcd#(true(),s(x),s(y)) -> gcd#(minus(x,y),s(y))

and R consists of:

r1: le(|0|(),y) -> true()
r2: le(s(x),|0|()) -> false()
r3: le(s(x),s(y)) -> le(x,y)
r4: pred(s(x)) -> x
r5: minus(x,|0|()) -> x
r6: minus(x,s(y)) -> pred(minus(x,y))
r7: gcd(|0|(),y) -> y
r8: gcd(s(x),|0|()) -> s(x)
r9: gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
r10: if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
r11: if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))
r12: rand(x) -> x
r13: rand(x) -> rand(s(x))

The set of usable rules consists of

  r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, r11, r12, r13

Take the reduction pair:

  lexicographic combination of reduction pairs:
  
    1. weighted path order
    
      base order:
    
        matrix interpretations:
        
          carrier: N^2
          order: standard order
          interpretations:
            if_gcd#_A(x1,x2,x3) = ((1,0),(0,0)) x1 + ((1,0),(0,0)) x2 + x3 + (1,0)
            false_A() = (1,0)
            s_A(x1) = ((1,1),(0,0)) x1
            gcd#_A(x1,x2) = ((1,0),(0,0)) x1 + ((1,0),(0,0)) x2 + (2,0)
            minus_A(x1,x2) = ((1,1),(1,1)) x1 + (0,3)
            le_A(x1,x2) = ((0,0),(1,0)) x2 + (1,4)
            true_A() = (1,2)
            |0|_A() = (2,1)
            pred_A(x1) = ((1,0),(1,0)) x1 + (0,1)
            gcd_A(x1,x2) = ((1,0),(0,0)) x1 + x2 + (2,3)
            if_gcd_A(x1,x2,x3) = ((1,0),(0,0)) x2 + ((1,0),(0,0)) x3 + (2,3)
            rand_A(x1) = ((1,1),(0,1)) x1 + (1,1)
    
      precedence:
      
        if_gcd# = false = s = gcd# = minus = le = true = |0| = pred = gcd = if_gcd = rand
      
      partial status:
    
        pi(if_gcd#) = []
        pi(false) = []
        pi(s) = []
        pi(gcd#) = []
        pi(minus) = []
        pi(le) = []
        pi(true) = []
        pi(|0|) = []
        pi(pred) = []
        pi(gcd) = []
        pi(if_gcd) = []
        pi(rand) = []
    
    2. weighted path order
    
      base order:
    
        matrix interpretations:
        
          carrier: N^2
          order: standard order
          interpretations:
            if_gcd#_A(x1,x2,x3) = ((1,1),(0,0)) x1 + x2 + ((0,1),(0,1)) x3 + (5,0)
            false_A() = (2,3)
            s_A(x1) = ((1,1),(1,1)) x1 + (9,4)
            gcd#_A(x1,x2) = ((1,1),(0,1)) x1 + x2 + (1,0)
            minus_A(x1,x2) = x1 + (7,2)
            le_A(x1,x2) = (2,3)
            true_A() = (1,1)
            |0|_A() = (3,4)
            pred_A(x1) = x1
            gcd_A(x1,x2) = ((0,1),(1,0)) x1 + x2 + (1,5)
            if_gcd_A(x1,x2,x3) = ((0,1),(1,0)) x2 + ((0,1),(1,0)) x3 + (5,0)
            rand_A(x1) = (0,0)
    
      precedence:
      
        if_gcd > minus = |0| = pred > gcd > if_gcd# = false = s = gcd# = le = true = rand
      
      partial status:
    
        pi(if_gcd#) = []
        pi(false) = []
        pi(s) = []
        pi(gcd#) = [1]
        pi(minus) = [1]
        pi(le) = []
        pi(true) = []
        pi(|0|) = []
        pi(pred) = []
        pi(gcd) = []
        pi(if_gcd) = []
        pi(rand) = []
    

The next rules are strictly ordered:

  p1

We remove them from the problem.

-- SCC decomposition.

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

p1: gcd#(s(x),s(y)) -> if_gcd#(le(y,x),s(x),s(y))
p2: if_gcd#(true(),s(x),s(y)) -> gcd#(minus(x,y),s(y))

and R consists of:

r1: le(|0|(),y) -> true()
r2: le(s(x),|0|()) -> false()
r3: le(s(x),s(y)) -> le(x,y)
r4: pred(s(x)) -> x
r5: minus(x,|0|()) -> x
r6: minus(x,s(y)) -> pred(minus(x,y))
r7: gcd(|0|(),y) -> y
r8: gcd(s(x),|0|()) -> s(x)
r9: gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
r10: if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
r11: if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))
r12: rand(x) -> x
r13: rand(x) -> rand(s(x))

The estimated dependency graph contains the following SCCs:

  {p1, p2}


-- Reduction pair.

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

p1: gcd#(s(x),s(y)) -> if_gcd#(le(y,x),s(x),s(y))
p2: if_gcd#(true(),s(x),s(y)) -> gcd#(minus(x,y),s(y))

and R consists of:

r1: le(|0|(),y) -> true()
r2: le(s(x),|0|()) -> false()
r3: le(s(x),s(y)) -> le(x,y)
r4: pred(s(x)) -> x
r5: minus(x,|0|()) -> x
r6: minus(x,s(y)) -> pred(minus(x,y))
r7: gcd(|0|(),y) -> y
r8: gcd(s(x),|0|()) -> s(x)
r9: gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
r10: if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
r11: if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))
r12: rand(x) -> x
r13: rand(x) -> rand(s(x))

The set of usable rules consists of

  r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, r11, r12, r13

Take the reduction pair:

  lexicographic combination of reduction pairs:
  
    1. weighted path order
    
      base order:
    
        matrix interpretations:
        
          carrier: N^2
          order: standard order
          interpretations:
            gcd#_A(x1,x2) = ((1,0),(0,0)) x1 + ((1,0),(0,0)) x2 + (3,1)
            s_A(x1) = ((1,1),(0,0)) x1
            if_gcd#_A(x1,x2,x3) = ((1,1),(0,1)) x2 + ((1,0),(0,0)) x3 + (3,1)
            le_A(x1,x2) = ((1,1),(0,0)) x2 + (2,2)
            true_A() = (1,2)
            minus_A(x1,x2) = ((1,0),(1,1)) x1 + (0,4)
            |0|_A() = (2,1)
            false_A() = (2,2)
            pred_A(x1) = ((1,0),(1,0)) x1 + (0,1)
            gcd_A(x1,x2) = ((1,0),(1,0)) x1 + ((1,0),(1,1)) x2 + (3,3)
            if_gcd_A(x1,x2,x3) = ((0,1),(0,0)) x1 + ((1,0),(1,0)) x2 + ((1,0),(1,0)) x3 + (1,3)
            rand_A(x1) = ((1,1),(0,1)) x1 + (1,1)
    
      precedence:
      
        gcd# = s = if_gcd# = le = true = minus = |0| = false = pred = gcd = if_gcd = rand
      
      partial status:
    
        pi(gcd#) = []
        pi(s) = []
        pi(if_gcd#) = []
        pi(le) = []
        pi(true) = []
        pi(minus) = []
        pi(|0|) = []
        pi(false) = []
        pi(pred) = []
        pi(gcd) = []
        pi(if_gcd) = []
        pi(rand) = []
    
    2. weighted path order
    
      base order:
    
        matrix interpretations:
        
          carrier: N^2
          order: standard order
          interpretations:
            gcd#_A(x1,x2) = ((0,1),(0,1)) x1 + (8,10)
            s_A(x1) = ((1,0),(1,1)) x1 + (17,10)
            if_gcd#_A(x1,x2,x3) = ((0,1),(0,1)) x2 + (0,1)
            le_A(x1,x2) = (16,0)
            true_A() = (15,0)
            minus_A(x1,x2) = x1 + (1,1)
            |0|_A() = (0,0)
            false_A() = (1,0)
            pred_A(x1) = x1
            gcd_A(x1,x2) = ((1,1),(0,1)) x1 + ((0,1),(0,1)) x2 + (2,0)
            if_gcd_A(x1,x2,x3) = ((1,1),(0,1)) x2 + ((0,1),(0,1)) x3 + (1,0)
            rand_A(x1) = (0,0)
    
      precedence:
      
        if_gcd > gcd > le > gcd# = s = if_gcd# = true = minus = |0| = false = pred = rand
      
      partial status:
    
        pi(gcd#) = []
        pi(s) = []
        pi(if_gcd#) = []
        pi(le) = []
        pi(true) = []
        pi(minus) = [1]
        pi(|0|) = []
        pi(false) = []
        pi(pred) = []
        pi(gcd) = []
        pi(if_gcd) = [2]
        pi(rand) = []
    

The next rules are strictly ordered:

  p1

We remove them from the problem.

-- SCC decomposition.

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

p1: if_gcd#(true(),s(x),s(y)) -> gcd#(minus(x,y),s(y))

and R consists of:

r1: le(|0|(),y) -> true()
r2: le(s(x),|0|()) -> false()
r3: le(s(x),s(y)) -> le(x,y)
r4: pred(s(x)) -> x
r5: minus(x,|0|()) -> x
r6: minus(x,s(y)) -> pred(minus(x,y))
r7: gcd(|0|(),y) -> y
r8: gcd(s(x),|0|()) -> s(x)
r9: gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
r10: if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
r11: if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))
r12: rand(x) -> x
r13: rand(x) -> rand(s(x))

The estimated dependency graph contains the following SCCs:

  (no SCCs)

-- Reduction pair.

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

p1: le#(s(x),s(y)) -> le#(x,y)

and R consists of:

r1: le(|0|(),y) -> true()
r2: le(s(x),|0|()) -> false()
r3: le(s(x),s(y)) -> le(x,y)
r4: pred(s(x)) -> x
r5: minus(x,|0|()) -> x
r6: minus(x,s(y)) -> pred(minus(x,y))
r7: gcd(|0|(),y) -> y
r8: gcd(s(x),|0|()) -> s(x)
r9: gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
r10: if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
r11: if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))
r12: rand(x) -> x
r13: rand(x) -> rand(s(x))

The set of usable rules consists of

  r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, r11, r12, r13

Take the reduction pair:

  lexicographic combination of reduction pairs:
  
    1. weighted path order
    
      base order:
    
        max/plus interpretations on natural numbers:
        
          le#_A(x1,x2) = x2 + 1
          s_A(x1) = x1
          le_A(x1,x2) = max{8, x1 + 7, x2 + 6}
          |0|_A = 0
          true_A = 5
          false_A = 3
          pred_A(x1) = x1
          minus_A(x1,x2) = max{x1, x2}
          gcd_A(x1,x2) = max{x1 + 6, x2 + 6}
          if_gcd_A(x1,x2,x3) = max{x1 - 2, x2 + 6, x3 + 6}
          rand_A(x1) = x1 + 2
    
      precedence:
      
        false > gcd = if_gcd > |0| > le > minus > s > le# = pred > true = rand
      
      partial status:
    
        pi(le#) = [2]
        pi(s) = [1]
        pi(le) = [1, 2]
        pi(|0|) = []
        pi(true) = []
        pi(false) = []
        pi(pred) = [1]
        pi(minus) = [1, 2]
        pi(gcd) = []
        pi(if_gcd) = []
        pi(rand) = []
    
    2. weighted path order
    
      base order:
    
        max/plus interpretations on natural numbers:
        
          le#_A(x1,x2) = max{6, x2}
          s_A(x1) = 0
          le_A(x1,x2) = 25
          |0|_A = 0
          true_A = 1
          false_A = 1
          pred_A(x1) = max{10, x1}
          minus_A(x1,x2) = x1 + 10
          gcd_A(x1,x2) = 8
          if_gcd_A(x1,x2,x3) = 8
          rand_A(x1) = 1
    
      precedence:
      
        minus > pred = gcd = if_gcd > le# = le = |0| = true = false = rand > s
      
      partial status:
    
        pi(le#) = [2]
        pi(s) = []
        pi(le) = []
        pi(|0|) = []
        pi(true) = []
        pi(false) = []
        pi(pred) = []
        pi(minus) = [1]
        pi(gcd) = []
        pi(if_gcd) = []
        pi(rand) = []
    

The next rules are strictly ordered:

  p1

We remove them from the problem.  Then no dependency pair remains.

-- Reduction pair.

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

p1: minus#(x,s(y)) -> minus#(x,y)

and R consists of:

r1: le(|0|(),y) -> true()
r2: le(s(x),|0|()) -> false()
r3: le(s(x),s(y)) -> le(x,y)
r4: pred(s(x)) -> x
r5: minus(x,|0|()) -> x
r6: minus(x,s(y)) -> pred(minus(x,y))
r7: gcd(|0|(),y) -> y
r8: gcd(s(x),|0|()) -> s(x)
r9: gcd(s(x),s(y)) -> if_gcd(le(y,x),s(x),s(y))
r10: if_gcd(true(),s(x),s(y)) -> gcd(minus(x,y),s(y))
r11: if_gcd(false(),s(x),s(y)) -> gcd(minus(y,x),s(x))
r12: rand(x) -> x
r13: rand(x) -> rand(s(x))

The set of usable rules consists of

  r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, r11, r12, r13

Take the reduction pair:

  lexicographic combination of reduction pairs:
  
    1. weighted path order
    
      base order:
    
        max/plus interpretations on natural numbers:
        
          minus#_A(x1,x2) = max{3, x1 + 1, x2 + 1}
          s_A(x1) = max{2, x1}
          le_A(x1,x2) = max{x1 + 17, x2 + 5}
          |0|_A = 10
          true_A = 9
          false_A = 16
          pred_A(x1) = max{1, x1}
          minus_A(x1,x2) = max{2, x1, x2}
          gcd_A(x1,x2) = max{x1 + 4, x2 + 4}
          if_gcd_A(x1,x2,x3) = max{x2 + 4, x3 + 4}
          rand_A(x1) = max{6, x1 + 3}
    
      precedence:
      
        true > minus# = le = false = minus = gcd = if_gcd > s = |0| > pred = rand
      
      partial status:
    
        pi(minus#) = [2]
        pi(s) = [1]
        pi(le) = []
        pi(|0|) = []
        pi(true) = []
        pi(false) = []
        pi(pred) = [1]
        pi(minus) = [1, 2]
        pi(gcd) = []
        pi(if_gcd) = []
        pi(rand) = []
    
    2. weighted path order
    
      base order:
    
        max/plus interpretations on natural numbers:
        
          minus#_A(x1,x2) = max{5, x2}
          s_A(x1) = 3
          le_A(x1,x2) = 18
          |0|_A = 3
          true_A = 4
          false_A = 4
          pred_A(x1) = max{17, x1}
          minus_A(x1,x2) = 17
          gcd_A(x1,x2) = 17
          if_gcd_A(x1,x2,x3) = 17
          rand_A(x1) = 1
    
      precedence:
      
        gcd = if_gcd > minus# = s = le = |0| = true = false = pred = minus = rand
      
      partial status:
    
        pi(minus#) = [2]
        pi(s) = []
        pi(le) = []
        pi(|0|) = []
        pi(true) = []
        pi(false) = []
        pi(pred) = []
        pi(minus) = []
        pi(gcd) = []
        pi(if_gcd) = []
        pi(rand) = []
    

The next rules are strictly ordered:

  p1

We remove them from the problem.  Then no dependency pair remains.