def test_solver_constrained_unsatisfiable():
domain = SignDomain(["a", "b", "c"])
state = SignAbstractState({
"a": Sign.Positive,
"b": Sign.Negative,
"c": Sign.Bottom
})
solution = domain.model(domain.gamma_hat(state))
assert solution is None
def test_solver_constrained_satisfiable():
domain = SignDomain(["a", "b", "c"])
state = SignAbstractState({
"a": Sign.Positive,
"b": Sign.Negative,
"c": Sign.Positive
})
solution = domain.model(domain.gamma_hat(state))
assert solution is not None
assert solution.value_of("a") > 0
assert solution.value_of("b") < 0
assert solution.value_of("c") > 0
def test_RSY_post_hat_add_subtract():
"""Here, we add the knowledge of the input state
"""
domain = SignDomain(["x", "x'", "x''"])
x = domain.z3_variable("x")
xp = domain.z3_variable("x'")
xpp = domain.z3_variable("x''")
phi = z3.And(xp == x - 5, xpp == xp + 5)
# This is where we add our supposition about the input
state = SignAbstractState({
"x": Sign.Positive,
"x'": Sign.Top,
"x''": Sign.Top
})
phi = z3.And(domain.gamma_hat(state), phi)
post_hat = RSY(domain, phi)
assert post_hat.sign_of("x") == Sign.Positive
assert post_hat.sign_of("x'") == Sign.Top
assert post_hat.sign_of("x''") == Sign.Positive