YES
0 RelTRS
↳1 RelTRStoRelADPProof (⇔, 0 ms)
↳2 RelADPP
↳3 RelADPDepGraphProof (⇔, 0 ms)
↳4 RelADPP
↳5 RelADPCleverAfsProof (⇒, 49 ms)
↳6 QDP
↳7 MRRProof (⇔, 0 ms)
↳8 QDP
↳9 MRRProof (⇔, 4 ms)
↳10 QDP
↳11 QDPBoundsTAProof (⇔, 0 ms)
↳12 QDP
↳13 PisEmptyProof (⇔, 0 ms)
↳14 YES
tests(0) → true
tests(s(x)) → and(test(rands(rand(0), nil)), x)
test(done(y)) → eq(f(y), g(y))
eq(x, x) → true
rands(0, y) → done(y)
rands(s(x), y) → rands(x, ::(rand(0), y))
rand(x) → rand(s(x))
rand(x) → x
We upgrade the RelTRS problem to an equivalent Relative ADP Problem [IJCAR24].
tests(0) → true
tests(s(x)) → and(TEST(rands(rand(0), nil)), x)
tests(s(x)) → and(test(RANDS(rand(0), nil)), x)
tests(s(x)) → and(test(rands(RAND(0), nil)), x)
test(done(y)) → EQ(f(y), g(y))
eq(x, x) → true
rands(0, y) → done(y)
rands(s(x), y) → RANDS(x, ::(rand(0), y))
rands(s(x), y) → rands(x, ::(RAND(0), y))
rand(x) → RAND(s(x))
rand(x) → x
We use the relative dependency graph processor [IJCAR24].
The approximation of the Relative Dependency Graph contains:
1 SCC with nodes from P_abs,
0 Lassos,
Result: This relative DT problem is equivalent to 1 subproblem.
tests(s(x)) → and(test(rands(rand(0), nil)), x)
rands(0, y) → done(y)
rands(s(x), y) → RANDS(x, ::(rand(0), y))
rands(s(x), y) → rands(x, ::(rand(0), y))
test(done(y)) → eq(f(y), g(y))
tests(0) → true
eq(x, x) → true
rand(x) → rand(s(x))
rand(x) → x
Furthermore, We use an argument filter [LPAR04].
Filtering:rands_2 =
true =
done_1 =
and_2 = 0, 1
rand_1 =
RANDS_2 = 1
g_1 =
nil =
s_1 =
eq_2 = 0, 1
::_2 = 1
tests_1 = 0
f_1 =
0 =
test_1 = 0
Found this filtering by looking at the following order that orders at least one DP strictly:Combined order from the following AFS and order.
RANDS(x1, x2) = RANDS(x1)
s(x1) = s(x1)
::(x1, x2) = x1
rand(x1) = x1
0 = 0
tests(x1) = tests
and(x1, x2) = and
test(x1) = test
rands(x1, x2) = rands(x1, x2)
nil = nil
done(x1) = x1
eq(x1, x2) = eq
f(x1) = f(x1)
g(x1) = g(x1)
true = true
Recursive path order with status [RPO].
Quasi-Precedence:
[test, f1] > [tests, eq, true] > [s1, and] > RANDS1
[test, f1] > [tests, eq, true] > 0
[test, f1] > [tests, eq, true] > nil
[test, f1] > g1
rands2 > 0
RANDS1: multiset
s1: multiset
0: multiset
tests: []
and: multiset
test: []
rands2: [1,2]
nil: multiset
eq: []
f1: multiset
g1: multiset
true: multiset
RANDS(s0(x)) → RANDS(x)
tests → and
rands0(00, y) → done0(y)
rands0(s0(x), y) → rands0(x, ::(rand0(00)))
test → eq
tests → true0
rand0(x) → rand0(s0(x))
eq → true0
rand0(x) → x
rands0(00, y) → done0(y)
test → eq
tests → true0
POL(00) = 0
POL(::(x1)) = x1
POL(RANDS(x1)) = x1
POL(and) = 2
POL(done0(x1)) = 1 + x1
POL(eq) = 0
POL(rand0(x1)) = x1
POL(rands0(x1, x2)) = 2 + x1 + x2
POL(s0(x1)) = x1
POL(test) = 2
POL(tests) = 2
POL(true0) = 0
RANDS(s0(x)) → RANDS(x)
tests → and
rands0(s0(x), y) → rands0(x, ::(rand0(00)))
rand0(x) → rand0(s0(x))
eq → true0
rand0(x) → x
tests → and
eq → true0
POL(00) = 0
POL(::(x1)) = x1
POL(RANDS(x1)) = x1
POL(and) = 0
POL(eq) = 2
POL(rand0(x1)) = x1
POL(rands0(x1, x2)) = x1 + x2
POL(s0(x1)) = x1
POL(tests) = 2
POL(true0) = 1
RANDS(s0(x)) → RANDS(x)
rands0(s0(x), y) → rands0(x, ::(rand0(00)))
rand0(x) → rand0(s0(x))
rand0(x) → x
by considering the usable rules:
RANDS(s0(x)) → RANDS(x)
rands0(s0(x), y) → rands0(x, ::(rand0(00)))
rand0(x) → rand0(s0(x))
rand0(x) → x