def test_mk_observable_vars(self):
enc = master_be_fsm().encoding
# if a non existing var name is passed, an exception is thrown
with self.assertRaises(ValueError):
diagnosability.mk_observable_vars(["a"])
observable = diagnosability.mk_observable_vars(["status"])
self.assertEqual(observable, [enc.by_name["status.1"], enc.by_name["status.0"]])
def test_verify_exactly(self):
theta = Node.from_ptr(parse_simple_expression("TRUE"))
theta = bmcutils.make_nnf_boolean_wff(theta)
sigma_12= Node.from_ptr(parse_ltl_spec("TRUE"))
sigma_12= bmcutils.make_nnf_boolean_wff(sigma_12).to_node()
obs_names = ["mouse"]
obs_vars = diagnosability.mk_observable_vars(obs_names)
f1 = Node.from_ptr(parse_simple_expression("status = active"))
f2 = Node.from_ptr(parse_simple_expression("status = inactive"))
for i in range(5):
res = diagnosability.verify_for_size_exactly_k(obs_names, obs_vars, (f1, f2), i, theta, sigma_12, sigma_12)
self.assertEqual("No Violation", res)
f1 = Node.from_ptr(parse_simple_expression("status = active"))
f2 = Node.from_ptr(parse_simple_expression("status = highlight"))
res = diagnosability.verify_for_size_exactly_k(obs_names, obs_vars, (f1, f2), 0, theta, sigma_12, sigma_12)
self.assertEqual("No Violation", res)
res = diagnosability.verify_for_size_exactly_k(obs_names, obs_vars, (f1, f2), 1, theta, sigma_12, sigma_12)
self.assertTrue(res.startswith("############### DIAGNOSABILITY VIOLATION"))
res = diagnosability.verify_for_size_exactly_k(obs_names, obs_vars, (f1, f2), 2, theta, sigma_12, sigma_12)
self.assertTrue(res.startswith("############### DIAGNOSABILITY VIOLATION"))
res = diagnosability.verify_for_size_exactly_k(obs_names, obs_vars, (f1, f2), 3, theta, sigma_12, sigma_12)
self.assertTrue(res.startswith("############### DIAGNOSABILITY VIOLATION"))
def test_generate_sat_problem(self):
theta = Node.from_ptr(parse_simple_expression("TRUE"))
theta = bmcutils.make_nnf_boolean_wff(theta)
sigma_12= Node.from_ptr(parse_ltl_spec("TRUE"))
sigma_12= bmcutils.make_nnf_boolean_wff(sigma_12).to_node()
observable = diagnosability.mk_observable_vars(["mouse"])
f1 = Node.from_ptr(parse_simple_expression("status = active"))
f2 = Node.from_ptr(parse_simple_expression("status = inactive"))
for i in range(5):
problem = diagnosability.generate_sat_problem(observable, (f1, f2), i, theta, sigma_12, sigma_12)
solver = SatSolverFactory.create()
cnf = problem.to_cnf()
solver += cnf
solver.polarity(cnf, Polarity.POSITIVE)
self.assertEqual(SatSolverResult.UNSATISFIABLE, solver.solve())
f1 = Node.from_ptr(parse_simple_expression("status = active"))
f2 = Node.from_ptr(parse_simple_expression("status = highlight"))
for i in range(1, 4):
# length zero has no input => only an initial state and the
# diagnosability condition is not checked
problem = diagnosability.generate_sat_problem(observable, (f1, f2), i, theta, sigma_12, sigma_12)
solver = SatSolverFactory.create()
cnf = problem.to_cnf()
solver += cnf
solver.polarity(cnf, Polarity.POSITIVE)
self.assertEqual(SatSolverResult.SATISFIABLE, solver.solve())
def test_constraint_same_observations(self):
observable = diagnosability.mk_observable_vars(["mouse"])
constraint = diagnosability.constraint_same_observations(observable, 0, 5, 5)
model = bmcutils.BmcModel()
manual = Be.true(model._fsm.encoding.manager)
for i in range(6): # because we want to go from 0 through 5
for v in model._fsm.encoding.input_variables:
v_1 = v.at_time[i].boolean_expression
v_2 = v.at_time[5+i].boolean_expression
manual &= v_1.iff(v_2)
self.assertEqual(manual, constraint)