def test_iter(self):
"""tests the behavior of assign and value"""
with BmcSupport():
sexp_fsm = master_bool_sexp_fsm()
be_fsm = master_be_fsm()
# empty trace
trace = Trace.create(
"Dummy example",
TraceType.COUNTER_EXAMPLE,
sexp_fsm.symbol_table,
sexp_fsm.symbols_list,
is_volatile=True,
)
step1 = trace.steps[1]
yes = Node.from_ptr(parse_simple_expression("TRUE"))
no = Node.from_ptr(parse_simple_expression("FALSE"))
v = be_fsm.encoding.by_name["v"].name
self.assertEqual([], list(step1))
step1 += v, yes
self.assertEqual([(v, yes)], list(step1))
# += really ASSIGNS a value, not append
step1 += v, no
self.assertEqual([(v, no)], list(step1))
def test_bounded_semantics_without_loop(self):
# parse the ltl property
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.bounded_semantics_without_loop(self.fsm, spec, bound=-1)
# verify that the generated expression corresponds to what is announced
no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
# globally w/o loop is false (this is just a test)
self.assertEqual(no_loop, Be.false(self.fsm.encoding.manager))
# an other more complex generation
spec = Node.from_ptr(parse_ltl_spec("F (y <= 7)"))
no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
#
# The generated expression is [[f]]^{0}_{k} so (! L_{k}) is not taken
# care of. And actually, NuSMV does not generate that part of the
# formula: it only enforce the loop condition when the semantics with
# loop is used
#
handcrafted = Be.false(self.fsm.encoding.manager)
y_le_seven = Wff(parse_ltl_spec("y <= 7")).to_boolean_wff().to_be(self.fsm.encoding)
for time_x in reversed(range(11)): # 11 because range 'eats' up the last step
handcrafted |= self.fsm.encoding.shift_to_time(y_le_seven, time_x)
#### debuging info #####
#print("noloop = {}".format(no_loop.to_cnf()))
#print("hancraft= {}".format(handcrafted.to_cnf()))
#print(self.fsm.encoding)
self.assertEqual(no_loop, handcrafted)
def test_assign_value__magicmethod__(self):
"""tests the behavior of assign and value"""
with BmcSupport():
sexp_fsm = master_bool_sexp_fsm()
be_fsm = master_be_fsm()
# empty trace
trace = Trace.create(
"Dummy example",
TraceType.COUNTER_EXAMPLE,
sexp_fsm.symbol_table,
sexp_fsm.symbols_list,
is_volatile=True,
)
step1 = trace.steps[1]
yes = Node.from_ptr(parse_simple_expression("TRUE"))
no = Node.from_ptr(parse_simple_expression("FALSE"))
v = be_fsm.encoding.by_name["v"].name
self.assertIsNone(step1.value[v])
step1 += (v, yes)
self.assertEqual(yes, step1.value[v])
step1 += (v, no)
self.assertEqual(no, step1.value[v])
def test_generate_problem_with_fairness(self):
'''
This test clearly shows the difference in validating a property with
or without fairness constraint
'''
with tests.Configure(self, __file__, "/philo.smv"):
# length 0
# nusmv has fairness always on.
fml_node= Node.from_ptr(parse_ltl_spec("G (p1.waiting -> F !p1.waiting)"))
smv = ltlspec.generate_ltl_problem(self.befsm, fml_node, 0)
self.assertEqual(SatSolverResult.UNSATISFIABLE, self.satisfiability(smv))
formula = parseLTL("[](p1.waiting => <>!p1.waiting)")
unfair = gen.generate_problem(formula, self.befsm, 0, no_fairness=True)
self.assertEqual(SatSolverResult.UNSATISFIABLE, self.satisfiability(unfair))
fair = gen.generate_problem(formula, self.befsm, 0, no_fairness=False)
self.assertEqual(SatSolverResult.UNSATISFIABLE, self.satisfiability(fair))
# length 1
fml_node= Node.from_ptr(parse_ltl_spec("G (p1.waiting -> F !p1.waiting)"))
smv = ltlspec.generate_ltl_problem(self.befsm, fml_node, 1)
self.assertEqual(SatSolverResult.UNSATISFIABLE, self.satisfiability(smv))
formula = parseLTL("[](p1.waiting => <>!p1.waiting)")
unfair = gen.generate_problem(formula, self.befsm, 1, no_fairness=True)
self.assertEqual(SatSolverResult.SATISFIABLE, self.satisfiability(unfair))
fair = gen.generate_problem(formula, self.befsm, 1, no_fairness=False)
self.assertEqual(SatSolverResult.UNSATISFIABLE, self.satisfiability(fair))
def test_next_with_loop(self):
with tests.Configure(self, __file__, "/example.smv"):
i,k,l = 0,2,0
enc = self.enc
# One step
a = ast.Proposition("a")
formula = ast.Next(a)
tool = formula.semantic_with_loop(enc, i, k, l)
manual = a.semantic_with_loop(enc, 1, k, l)
nusmv = ltlspec.bounded_semantics(self.befsm,
Node.from_ptr(parse_ltl_spec("X a")),
bound = k,
loop = l)
loop_cond = bmcutils.loop_condition(enc, k, l)
s_tool = tests.canonical_cnf(tool & loop_cond)
s_manual= tests.canonical_cnf(manual & loop_cond)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_tool, s_nusmv)
self.assertEqual(s_tool, s_manual)
# two steps
formula = ast.Next(ast.Next(a))
tool = formula.semantic_with_loop(enc, i, k, l)
manual = a.semantic_with_loop(enc, 0, k, l)
nusmv = ltlspec.bounded_semantics(self.befsm,
Node.from_ptr(parse_ltl_spec("X X a")),
bound = k,
loop = l)
loop_cond = bmcutils.loop_condition(enc, k, l)
s_tool = tests.canonical_cnf(tool & loop_cond)
s_manual= tests.canonical_cnf(manual & loop_cond)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_tool, s_nusmv)
self.assertEqual(s_tool, s_manual)
# Three steps (getting over k)
formula = ast.Next(ast.Next(ast.Next(a)))
tool = formula.semantic_with_loop(enc, i, k, l)
manual = a.semantic_with_loop(enc, 1, k, l)
nusmv = ltlspec.bounded_semantics(self.befsm,
Node.from_ptr(parse_ltl_spec("X X X a")),
bound = k,
loop = l)
loop_cond = bmcutils.loop_condition(enc, k, l)
s_tool = tests.canonical_cnf(tool & loop_cond)
s_manual= tests.canonical_cnf(manual & loop_cond)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_tool, s_nusmv)
self.assertEqual(s_tool, s_manual)
def test_is_constant_expr(self):
expr = Node.from_ptr(parse_ltl_spec("F G ( w <-> v )"))
self.assertFalse(bmcutils.is_constant_expr(expr))
expr = Node.from_ptr(parse_ltl_spec("some_variable"))
self.assertFalse(bmcutils.is_constant_expr(expr))
expr = Node.from_ptr(parse_ltl_spec("TRUE"))
self.assertTrue(bmcutils.is_constant_expr(expr))
expr = Node.from_ptr(parse_ltl_spec("FALSE"))
self.assertTrue(bmcutils.is_constant_expr(expr))
def test_next_noloop(self):
with tests.Configure(self, __file__, "/example.smv"):
i,k = 0,2
enc = self.enc
# One step
a = ast.Proposition("a")
formula = ast.Next(a)
tool = formula.semantic_no_loop(enc, i, k)
manual = a.semantic_no_loop(enc, 1, k)
nusmv = ltlspec.bounded_semantics(self.befsm,
Node.from_ptr(parse_ltl_spec("X a")),
bound = k,
loop = bmcutils.no_loopback())
s_tool = tests.canonical_cnf(tool)
s_manual = tests.canonical_cnf(manual)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_tool, s_nusmv)
self.assertEqual(s_tool, s_manual)
# two steps
formula = ast.Next(ast.Next(a))
tool = formula.semantic_no_loop(enc, i, k)
manual = a.semantic_no_loop(enc, 2, k)
nusmv = ltlspec.bounded_semantics(self.befsm,
Node.from_ptr(parse_ltl_spec("X X a")),
bound = k,
loop = bmcutils.no_loopback())
s_tool = tests.canonical_cnf(tool)
s_manual = tests.canonical_cnf(manual)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_tool, s_nusmv)
self.assertEqual(s_tool, s_manual)
# Three steps (getting over k)
formula = ast.Next(ast.Next(ast.Next(a)))
tool = formula.semantic_no_loop(enc, i, k)
manual = Be.false(enc.manager)
nusmv = ltlspec.bounded_semantics(self.befsm,
Node.from_ptr(parse_ltl_spec("X X X a")),
bound = k,
loop = bmcutils.no_loopback())
s_tool = tests.canonical_cnf(tool)
s_manual = tests.canonical_cnf(manual)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_tool, s_nusmv)
self.assertEqual(s_tool, s_manual)
def test_is_variable(self):
expr = Node.from_ptr(parse_ltl_spec("F G ( w <-> v )"))
self.assertFalse(bmcutils.is_variable(expr))
expr = Node.from_ptr(parse_ltl_spec("some_variable"))
expr.type = _parser.DOT # just to make sure it is seen as a variable, not an atom
self.assertTrue(bmcutils.is_variable(expr))
expr = Node.from_ptr(parse_ltl_spec("TRUE"))
self.assertFalse(bmcutils.is_variable(expr))
expr = Node.from_ptr(parse_ltl_spec("FALSE"))
self.assertFalse(bmcutils.is_variable(expr))
def test_generate_problem_with_fairness(self):
'''
This test clearly shows the difference in validating a property with
or without fairness constraint
'''
with tests.Configure(self, __file__, "/philo.smv"):
# length 0
# nusmv has fairness always on.
fml_node = Node.from_ptr(
parse_ltl_spec("G (p1.waiting -> F !p1.waiting)"))
smv = ltlspec.generate_ltl_problem(self.befsm, fml_node, 0)
self.assertEqual(SatSolverResult.UNSATISFIABLE,
self.satisfiability(smv))
formula = parseLTL("[](p1.waiting => <>!p1.waiting)")
unfair = gen.generate_problem(formula,
self.befsm,
0,
no_fairness=True)
self.assertEqual(SatSolverResult.UNSATISFIABLE,
self.satisfiability(unfair))
fair = gen.generate_problem(formula,
self.befsm,
0,
no_fairness=False)
self.assertEqual(SatSolverResult.UNSATISFIABLE,
self.satisfiability(fair))
# length 1
fml_node = Node.from_ptr(
parse_ltl_spec("G (p1.waiting -> F !p1.waiting)"))
smv = ltlspec.generate_ltl_problem(self.befsm, fml_node, 1)
self.assertEqual(SatSolverResult.UNSATISFIABLE,
self.satisfiability(smv))
formula = parseLTL("[](p1.waiting => <>!p1.waiting)")
unfair = gen.generate_problem(formula,
self.befsm,
1,
no_fairness=True)
self.assertEqual(SatSolverResult.SATISFIABLE,
self.satisfiability(unfair))
fair = gen.generate_problem(formula,
self.befsm,
1,
no_fairness=False)
self.assertEqual(SatSolverResult.UNSATISFIABLE,
self.satisfiability(fair))
def validate_generate_problem(self, bound, custom_text, nusmv_text):
fsm = self.befsm
# formulae
formula = parseLTL(custom_text)
fml_node = Node.from_ptr(parse_ltl_spec(nusmv_text))
# IMPORTANT NOTE: each instantiation of the problem creates new CNF
# literal which appears in the clauses list (even in canonical form)
# hence, the canonical forms of the different instantiations cannot
# simply be compared as there is no a priori way to know what CNF
# literal reconcile with what other.
# However, the different expressions should all have the exact same
# satisfiability. So, that's how this test proceeds.
smv = ltlspec.generate_ltl_problem(fsm, fml_node, bound)
tool = gen.generate_problem(formula, fsm, bound)
manual = gen.model_problem(fsm, bound) &\
formula.nnf(True).bounded_semantics(fsm, bound)
sat_smv = self.satisfiability(smv)
sat_tool = self.satisfiability(tool)
sat_man = self.satisfiability(manual)
self.assertEqual(sat_tool, sat_man)
self.assertEqual(sat_tool, sat_smv)
def test_fill_counter_example(self):
load_from_string("""
MODULE main
VAR v : boolean;
w : boolean;
ASSIGN init(v) := TRUE;
next(v) := !v;
init(w) := FALSE;
next(w) := !w;
""")
with BmcSupport():
bound = 2
fsm = master_be_fsm()
sexpfsm = master_bool_sexp_fsm()
expr = Node.from_ptr(parse_ltl_spec("F ( w <-> v )"))
pb = generate_ltl_problem(fsm, expr, bound=bound)
cnf = pb.inline(True).to_cnf()
solver = SatSolverFactory.create()
solver += cnf
solver.polarity(cnf, Polarity.POSITIVE)
self.assertEqual(SatSolverResult.SATISFIABLE, solver.solve())
trace = Trace.create("FILLED", TraceType.COUNTER_EXAMPLE,
sexpfsm.symbol_table, sexpfsm.symbols_list,
True)
bmcutils.fill_counter_example(fsm, solver, bound, trace)
self.assertIsNotNone(trace)
self.assertEqual(2, len(trace))
print(trace)
def test_until_with_loop(self):
with tests.Configure(self, __file__, "/example.smv"):
enc = self.enc
i, k, l = 0, 2, 0
a = ast.Proposition("a")
b = ast.Proposition("b")
expr = ast.Until(a, b)
tool = expr.semantic_with_loop(enc, i, k, l)
manual = b.semantic_with_loop(enc, i, k, l) | \
(a.semantic_with_loop(enc, i, k, l) & b.semantic_with_loop(enc, i+1, k, l))
spec = Node.from_ptr(parse_ltl_spec("a U b"))
nusmv = ltlspec.bounded_semantics(self.befsm,
spec,
bound=k,
loop=l)
tool &= bmcutils.loop_condition(enc, k, l)
manual &= bmcutils.loop_condition(enc, k, l)
# normalized string representation of the BE's (make them comparable)
s_tool = tests.canonical_cnf(tool)
s_nusmv = tests.canonical_cnf(nusmv)
s_manual = tests.canonical_cnf(manual)
self.assertEqual(s_tool, s_manual)
self.assertEqual(s_tool, s_nusmv)
def decode_value(self, list_of_bits_and_value):
"""
Returns a node (:class:`pynusmv.node.Node`) corresponding to the value of
the variable encoded by the list of bits and values.
:param list_of_bits_and_value: a sequence of tuples (BeVar, BooleanValue)
which represent a bit and its value.
:return: an intelligible value node corresponding to what these bits
means when interpreted in the context of the SMV model.
"""
if not list_of_bits_and_value:
raise ValueError("The given list of bits and values must at least "+
"contain one bit")
# if the variable to be decoded is boolean in the model
if not list_of_bits_and_value[0][0].is_bit:
return list_of_bits_and_value[0][1]
# otherwise decode the bits
bool_enc = self._bool_enc
scalar = list_of_bits_and_value[0][0].scalar
bv = _bool.BitValues_create(bool_enc, scalar._ptr)
for bit,val in list_of_bits_and_value:
bit_index = _bool.BoolEnc_get_index_from_bit(bool_enc, bit.name._ptr)
_bool.BitValues_set(bv, bit_index, val)
result_ptr = _bool.BoolEnc_get_value_from_var_bits(bool_enc, bv)
_bool.BitValues_destroy(bv)
return Node.from_ptr(result_ptr)
def test_clear(self):
"""Verifies that clear works as expected"""
h = Assoc(_u.new_assoc(), freeit=True)
a = Node.from_ptr(parse_simple_expression("a.car = 3"), freeit=False)
h[a] = a
h.clear()
self.assertFalse(a in h)
def test_language_contains(self):
with BmcSupport():
sexp_fsm = master_bool_sexp_fsm()
be_fsm = master_be_fsm()
trace = Trace.create(
"Dummy example",
TraceType.COUNTER_EXAMPLE,
sexp_fsm.symbol_table,
sexp_fsm.symbols_list,
is_volatile=True,
)
v = be_fsm.encoding.by_name["v"]
w = be_fsm.encoding.by_name["w"]
f = be_fsm.encoding.by_name["f"]
i = be_fsm.encoding.by_name["i"]
self.assertTrue(v.name in trace)
self.assertTrue(w.name in trace)
self.assertTrue(f.name in trace)
self.assertTrue(i.name in trace)
x = parse_simple_expression("x")
self.assertFalse(Node.from_ptr(x) in trace)
def test_copy(self):
"""Tests the copy behavior"""
h = Assoc(_u.new_assoc(), freeit=True)
a = Node.from_ptr(parse_simple_expression("a.car = 3"), freeit=False)
h[a] = a
h2= h.copy()
self.assertTrue(a in h2)
def test_clear(self):
"""Verifies that clear works as expected"""
h = Assoc(_u.new_assoc(), freeit=True)
a = Node.from_ptr(parse_simple_expression("a.car = 3"), freeit=False)
h[a] = a
h.clear()
self.assertFalse(a in h)
def test_eventually_with_loop(self):
with tests.Configure(self, __file__, "/example.smv"):
i, k, l = 0, 2, 0
enc = self.enc
a = ast.Proposition("a")
formula = ast.Eventually(a)
tool = formula.semantic_with_loop(enc, i, k, l)
manual = a.semantic_with_loop(enc, i+1, k, l) |\
a.semantic_with_loop(enc, i , k, l)
nusmv = ltlspec.bounded_semantics(self.befsm,
Node.from_ptr(
parse_ltl_spec("F a")),
bound=k,
loop=l)
# normalized string representation of the BE's (make them comparable)
loop_cond = bmcutils.loop_condition(enc, k, l)
s_tool = tests.canonical_cnf(tool & loop_cond)
s_manual = tests.canonical_cnf(manual & loop_cond)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_nusmv, s_tool)
self.assertEqual(s_manual, s_tool)
def validate_generate_problem(self, bound, custom_text, nusmv_text):
fsm = self.befsm
# formulae
formula = parseLTL(custom_text)
fml_node= Node.from_ptr(parse_ltl_spec(nusmv_text))
# IMPORTANT NOTE: each instantiation of the problem creates new CNF
# literal which appears in the clauses list (even in canonical form)
# hence, the canonical forms of the different instantiations cannot
# simply be compared as there is no a priori way to know what CNF
# literal reconcile with what other.
# However, the different expressions should all have the exact same
# satisfiability. So, that's how this test proceeds.
smv = ltlspec.generate_ltl_problem(fsm, fml_node, bound)
tool = gen.generate_problem(formula, fsm, bound)
manual = gen.model_problem(fsm, bound) &\
formula.nnf(True).bounded_semantics(fsm, bound)
sat_smv = self.satisfiability(smv)
sat_tool= self.satisfiability(tool)
sat_man = self.satisfiability(manual)
self.assertEqual(sat_tool, sat_man)
self.assertEqual(sat_tool, sat_smv)
def test_bounded_semantics_with_loop(self):
# parse the ltl property
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.bounded_semantics_single_loop(self.fsm, spec, -1, -2)
# it must raise exception when the bound and loop are not consistent
with self.assertRaises(ValueError):
ltlspec.bounded_semantics_single_loop(self.fsm, spec, 5, 6)
# verify that the generated problem corresponds to what is announced
# without optimisation, the all loops is built as the conjunction of all
# the possible 'single_loops'
all_loops = ltlspec.bounded_semantics_all_loops(self.fsm,
spec,
10,
0,
optimized=False)
acc_loops = Be.false(self.fsm.encoding.manager)
for time_t in range(10):
acc_loops |= ltlspec.bounded_semantics_single_loop(
self.fsm, spec, 10, time_t)
self.assertEqual(acc_loops, all_loops)
# with optimisation, it's different
all_loops = ltlspec.bounded_semantics_all_loops(self.fsm,
spec,
10,
0,
optimized=True)
self.assertNotEqual(acc_loops, all_loops)
def test_weak_until_noloop(self):
with tests.Configure(self, __file__, "/example.smv"):
enc = self.enc
a = ast.Proposition("a")
b = ast.Proposition("b")
expr = ast.WeakUntil(a, b)
tool = expr.semantic_no_loop(enc, 0, 2)
manual = (b.semantic_no_loop(enc, 0, 2)
| (a.semantic_no_loop(enc, 0, 2) &
(b.semantic_no_loop(enc, 1, 2)
| (a.semantic_no_loop(enc, 1, 2) &
(b.semantic_no_loop(enc, 2, 2))))))
spec = Node.from_ptr(parse_ltl_spec("a U b"))
nusmv = ltlspec.bounded_semantics(self.befsm,
spec,
bound=2,
loop=bmcutils.no_loopback())
# normalized string representation of the BE's (make them comparable)
s_tool = tests.canonical_cnf(tool)
s_nusmv = tests.canonical_cnf(nusmv)
s_manual = tests.canonical_cnf(manual)
self.assertEqual(s_tool, s_manual)
self.assertEqual(s_tool, s_nusmv)
def test_constraint_context_sigma(self):
fsm = master_be_fsm()
_true = Node.from_ptr(parse_ltl_spec("TRUE"))
_true = bmcutils.make_nnf_boolean_wff(_true)
_truen= _true.to_node()
cond = Wff(parse_ltl_spec("G !(mouse = hover)"))\
.to_boolean_wff()\
.to_negation_normal_form()
off_1 = 0
off_2 = 2
length= 1
# sigma1
problem = diagnosability.generate_sat_problem([], (_truen, _truen), length, _true, cond.to_node(), _truen)
tm_cond = ltlspec.bounded_semantics_at_offset(fsm, cond.to_node(), length, off_1)
canonical_p = tests.canonical_cnf(problem)
canonical_f = tests.canonical_cnf(tm_cond)
self.assertTrue(all(clause in canonical_p for clause in canonical_f))
# sigma2
problem = diagnosability.generate_sat_problem([], (_truen, _truen), length, _true, _truen, cond.to_node())
tm_cond = ltlspec.bounded_semantics_at_offset(fsm, cond.to_node(), length, off_2)
canonical_p = tests.canonical_cnf(problem)
canonical_f = tests.canonical_cnf(tm_cond)
self.assertTrue(all(clause in canonical_p for clause in canonical_f))
def test_eventually_with_loop(self):
with tests.Configure(self, __file__, "/example.smv"):
i,k,l = 0,2,0
enc = self.enc
a = ast.Proposition("a")
formula = ast.Eventually(a)
tool = formula.semantic_with_loop(enc, i, k, l)
manual = a.semantic_with_loop(enc, i+1, k, l) |\
a.semantic_with_loop(enc, i , k, l)
nusmv = ltlspec.bounded_semantics(
self.befsm, Node.from_ptr(parse_ltl_spec("F a")),
bound = k,
loop = l)
# normalized string representation of the BE's (make them comparable)
loop_cond = bmcutils.loop_condition(enc, k, l)
s_tool = tests.canonical_cnf(tool & loop_cond)
s_manual= tests.canonical_cnf(manual & loop_cond)
s_nusmv = tests.canonical_cnf(nusmv)
self.assertEqual(s_nusmv, s_tool)
self.assertEqual(s_manual, s_tool)
def decode_value(self, list_of_bits_and_value):
"""
Returns a node (:see:`pynusmv.node.Node`) corresponding to the value of
the variable encoded by the list of bits and values.
:param list_of_bits_and_value: a sequence of tuples (BeVar, BooleanValue)
which represent a bit and its value.
:return: an intelligible value node corresponding to what these bits
means when interpreted in the context of the SMV model.
"""
if not list_of_bits_and_value:
raise ValueError("The given list of bits and values must at least "+
"contain one bit")
# if the variable to be decoded is boolean in the model
if not list_of_bits_and_value[0][0].is_bit:
return list_of_bits_and_value[0][1]
# otherwise decode the bits
bool_enc = self._bool_enc
scalar = list_of_bits_and_value[0][0].scalar
bv = _bool.BitValues_create(bool_enc, scalar._ptr)
for bit,val in list_of_bits_and_value:
bit_index = _bool.BoolEnc_get_index_from_bit(bool_enc, bit.name._ptr)
_bool.BitValues_set(bv, bit_index, val)
result_ptr = _bool.BoolEnc_get_value_from_var_bits(bool_enc, bv)
_bool.BitValues_destroy(bv)
return Node.from_ptr(result_ptr)
def test_until_with_loop(self):
with tests.Configure(self, __file__, "/example.smv"):
enc = self.enc
i,k,l= 0,2,0
a = ast.Proposition("a")
b = ast.Proposition("b")
expr = ast.Until(a, b)
tool = expr.semantic_with_loop(enc, i,k,l)
manual = b.semantic_with_loop(enc, i, k, l) | \
(a.semantic_with_loop(enc, i, k, l) & b.semantic_with_loop(enc, i+1, k, l))
spec = Node.from_ptr(parse_ltl_spec("a U b"))
nusmv = ltlspec.bounded_semantics(self.befsm, spec, bound=k, loop=l)
tool &= bmcutils.loop_condition(enc, k, l)
manual &= bmcutils.loop_condition(enc, k, l)
# normalized string representation of the BE's (make them comparable)
s_tool = tests.canonical_cnf(tool)
s_nusmv = tests.canonical_cnf(nusmv)
s_manual= tests.canonical_cnf(manual)
self.assertEqual(s_tool, s_manual)
self.assertEqual(s_tool, s_nusmv)
def test_concat(self):
with BmcSupport():
sexp_fsm = master_bool_sexp_fsm()
be_fsm = master_be_fsm()
trace = Trace.create("Dummy example",
TraceType.COUNTER_EXAMPLE,
sexp_fsm.symbol_table,
sexp_fsm.symbols_list,
is_volatile=True)
spec = Node.from_ptr(parse_ltl_spec("F (w <-> v)"))
bound = 2
problem = generate_ltl_problem(be_fsm, spec,
bound=bound) #.inline(True)
cnf = problem.to_cnf()
solver = SatSolverFactory.create()
solver += cnf
solver.polarity(cnf, Polarity.POSITIVE)
solver.solve()
other = generate_counter_example(be_fsm, problem, solver, bound)
trace.concat(other)
self.assertEquals(-1, trace.id)
self.assertFalse(trace.is_registered)
self.assertEquals("Dummy example", trace.description)
self.assertEquals(TraceType.COUNTER_EXAMPLE, trace.type)
self.assertTrue(trace.is_volatile)
self.assertEquals(2, trace.length)
self.assertEquals(2, len(trace))
self.assertFalse(trace.is_empty)
self.assertFalse(trace.is_frozen)
self.assertTrue(trace.is_thawed)
def test_copy(self):
"""Tests the copy behavior"""
h = Assoc(_u.new_assoc(), freeit=True)
a = Node.from_ptr(parse_simple_expression("a.car = 3"), freeit=False)
h[a] = a
h2 = h.copy()
self.assertTrue(a in h2)
def test_empty(self):
"""Tests the empty factory"""
a = Node.from_ptr(parse_simple_expression("a.car = 3"), freeit=False)
h = Assoc.empty(freeit=True)
self.assertFalse(a in h)
hh = Assoc.empty(initial_capa=1, freeit=True)
hh[a] = a
self.assertTrue(a in hh)
def name(self):
"""
Returns the name of this BOOLEAN variable. If this variable was not
declared boolean in the SMV text, this is going to be the name of one
of the bits composing that variable.
:return: the name node corresponding to this boolean variable.
"""
ptr = _be.BeEnc_index_to_name(self.encoding._ptr, self.untimed.index)
return Node.from_ptr(ptr)
def name(self):
"""
Returns the name of this BOOLEAN variable. If this variable was not
declared boolean in the SMV text, this is going to be the name of one
of the bits composing that variable.
:return: the name node corresponding to this boolean variable.
"""
ptr = _be.BeEnc_index_to_name(self.encoding._ptr, self.untimed.index)
return Node.from_ptr(ptr)
def test_associative_array(self):
"""
This function tests the basic functions of the associative array proto
"""
h = Assoc(_u.new_assoc(), freeit=True)
a = Node.from_ptr(parse_simple_expression("a.car = 3"), freeit=False)
b = Node.from_ptr(parse_simple_expression("b.car = 3"), freeit=False)
# __contains__
self.assertFalse(a in h)
# __setitem__
h[a] = a
self.assertTrue(a in h)
# __getitem__
self.assertEqual(h[a], a)
with self.assertRaises(KeyError):
h[b]
# __delitem__
del h[a]
self.assertFalse(a in h)
def __next__(self):
"""
Performs the iteration
:return: the next node
:raise: StopIteration when the iteration is over
"""
if self._ptr is None:
raise StopIteration
else:
ret = Node.from_ptr(self._ptr)
self._ptr = _node.cdr(self._ptr)
return ret
def cdr(this_node):
"""
Returns the rhs branch of this node.
.. note::
This is a simple workaround of `Node.cdr` which does not behave as expected.
:param this_node: the node whose rhs (cdr) is wanted.
:return: the rhs member of this node.
"""
return Node.from_ptr(_node.cdr(this_node._ptr))
def cdr(this_node):
"""
Returns the rhs branch of this node.
.. note::
This is a simple workaround of `Node.cdr` which does not behave as expected.
:param this_node: the node whose rhs (cdr) is wanted.
:return: the rhs member of this node.
"""
return Node.from_ptr(_node.cdr(this_node._ptr))
def __next__(self):
"""
Performs the iteration
:return: the next node
:raise: StopIteration when the iteration is over
"""
if self._ptr is None:
raise StopIteration
else:
ret = Node.from_ptr(self._ptr)
self._ptr = _node.cdr(self._ptr)
return ret
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_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_bounded_semantics_with_loop_optimized_depth1(self):
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )")) # depth == 1
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.bounded_semantics_all_loops_optimisation_depth1(self.fsm, spec, -1)
# should yield the same result (w/ opt) as regular all loops when depth is one
optimized = ltlspec.bounded_semantics_all_loops_optimisation_depth1(self.fsm, spec, 5)
regular = ltlspec.bounded_semantics_all_loops(self.fsm, spec, bound=5, loop=0)
self.assertEqual(regular, optimized)
# but not when the optim is turned off on 'all loops'
regular = ltlspec.bounded_semantics_all_loops(self.fsm, spec, bound=5, loop=0, optimized=False)
self.assertNotEqual(regular, optimized)
# and it should only be applied when the depth is equal to one
spec = Node.from_ptr(parse_ltl_spec("F G ( y <= 7 )")) # depth == 2
self.assertEqual(2, Wff.decorate(spec).depth)
optimized = ltlspec.bounded_semantics_all_loops_optimisation_depth1(self.fsm, spec, 5)
regular = ltlspec.bounded_semantics_all_loops(self.fsm, spec, bound=5, loop=0)
self.assertNotEqual(regular, optimized)
def validate_bounded_semantics(self, bound, custom_text, nusmv_text):
fsm = self.befsm
# formulae
formula = parseLTL(custom_text)
fml_node = Node.from_ptr(parse_ltl_spec(nusmv_text))
tool = formula.bounded_semantics(fsm, bound)
smv = ltlspec.bounded_semantics(fsm, fml_node, bound)
# canonical forms
s_tool = tests.canonical_cnf(tool)
s_smv = tests.canonical_cnf(smv)
self.assertEqual(s_tool, s_smv)
def test_eventually_critical_pair(self):
enc = master_be_fsm().encoding
f1 = Node.from_ptr(parse_simple_expression("status = active"))
f2 = Node.from_ptr(parse_simple_expression("status = highlight"))
constraint = diagnosability.constraint_eventually_critical_pair(
(f1, f2), 0, 5, 5)
nnf1 = bmcutils.make_nnf_boolean_wff(f1).to_be(enc)
nnf2 = bmcutils.make_nnf_boolean_wff(f2).to_be(enc)
manual = Be.false(enc.manager)
for i in range(6): # again, from 0 to 5
manual |= (enc.shift_to_time(nnf1, i)
& enc.shift_to_time(nnf2, 5 + i))
# observing the clauses generated in both cases, one observes that
# the generated clauses are the same except that the number of the cnf
# literals do not match, example:
# [-59, -24, 58]
# [-65, -24, 64]
# This is due to the fact that some 'fresh' cnf literals are used in the
# generation of the epxression. Therefore, a comparison (even on the
# canonical form of the CNF) is not feasible.
#
# Satisfiability is just an indication but at least that is .. something
solver_c = SatSolverFactory.create()
cnf = constraint.to_cnf()
solver_c += cnf
solver_c.polarity(cnf, Polarity.POSITIVE)
result_c = solver_c.solve()
solver_m = SatSolverFactory.create()
cnf = manual.to_cnf()
solver_m += cnf
solver_m.polarity(cnf, Polarity.POSITIVE)
result_m = solver_m.solve()
self.assertEqual(result_c, result_m)
def validate_bounded_semantics(self, bound, custom_text, nusmv_text):
fsm = self.befsm
# formulae
formula = parseLTL(custom_text)
fml_node= Node.from_ptr(parse_ltl_spec(nusmv_text))
tool = formula.bounded_semantics(fsm, bound)
smv = ltlspec.bounded_semantics(fsm, fml_node, bound)
# canonical forms
s_tool = tests.canonical_cnf(tool)
s_smv = tests.canonical_cnf(smv)
self.assertEqual(s_tool, s_smv)
def value(self, symbol_node):
"""
Retrieves the value that was assigned to `symbol_node` in the current
trace step.
:param symbol_node: a Node (:class:`pynusmv.node.Node`)
representing the symbol to which a value is assigned
:return: a value_node, that is to say a Node (:class:`pynusmv.node.Node`)
representing the value being assigned to the requested symbol.
"""
return Node.from_ptr(
_trace.Trace_step_get_value(self.trace._ptr, self._ptr,
symbol_node._ptr))
def test_eventually_critical_pair(self):
enc= master_be_fsm().encoding
f1 = Node.from_ptr(parse_simple_expression("status = active"))
f2 = Node.from_ptr(parse_simple_expression("status = highlight"))
constraint = diagnosability.constraint_eventually_critical_pair((f1, f2), 0, 5, 5)
nnf1 = bmcutils.make_nnf_boolean_wff(f1).to_be(enc)
nnf2 = bmcutils.make_nnf_boolean_wff(f2).to_be(enc)
manual = Be.false(enc.manager)
for i in range(6): # again, from 0 to 5
manual |= ( enc.shift_to_time(nnf1 , i)
& enc.shift_to_time(nnf2 , 5+i))
# observing the clauses generated in both cases, one observes that
# the generated clauses are the same except that the number of the cnf
# literals do not match, example:
# [-59, -24, 58]
# [-65, -24, 64]
# This is due to the fact that some 'fresh' cnf literals are used in the
# generation of the epxression. Therefore, a comparison (even on the
# canonical form of the CNF) is not feasible.
#
# Satisfiability is just an indication but at least that is .. something
solver_c = SatSolverFactory.create()
cnf = constraint.to_cnf()
solver_c+= cnf
solver_c.polarity(cnf, Polarity.POSITIVE)
result_c = solver_c.solve()
solver_m = SatSolverFactory.create()
cnf = manual.to_cnf()
solver_m+= cnf
solver_m.polarity(cnf, Polarity.POSITIVE)
result_m = solver_m.solve()
self.assertEqual(result_c, result_m)
def scalar(self):
"""
Returns the name node of this variable as it was declared in the SMV
text (hence not the name of the bit, but the name of the variable).
:see:`is_bit`
:return: the name node corresponding to scalar using this variable.
"""
bool_enc = self.encoding._bool_enc
if self.is_bit:
scalar = _bool.BoolEnc_get_scalar_var_from_bit(bool_enc, self.name._ptr)
return Node.from_ptr(scalar)
else:
return self.name
def scalar(self):
"""
Returns the name node of this variable as it was declared in the SMV
text (hence not the name of the bit, but the name of the variable).
.. seealso:: `is_bit`
:return: the name node corresponding to scalar using this variable.
"""
bool_enc = self.encoding._bool_enc
if self.is_bit:
scalar = _bool.BoolEnc_get_scalar_var_from_bit(bool_enc, self.name._ptr)
return Node.from_ptr(scalar)
else:
return self.name
def test_make_negated_nnf_boolean_wff(self):
load_from_string("""
MODULE main
VAR v : boolean;
w : boolean;
ASSIGN init(v) := TRUE;
next(v) := !v;
""")
with BmcSupport():
expr = Node.from_ptr(parse_ltl_spec("F G ( w <-> v )"))
wff = bmcutils.make_negated_nnf_boolean_wff(expr)
self.assertEquals(" F ( G (w <-> v))", str(expr))
# Via De Morgan Laws
self.assertEquals(" G ( F ((v & !w) | (!v & w)))", str(wff))
def value(self, symbol_node):
"""
Retrieves the value that was assigned to `symbol_node` in the current
trace step.
:param symbol_node: a Node (:see: :class: `pynusmv.node.Node`)
representing the symbol to which a value is assigned
:return: a value_node, that is to say a Node (:see: :class: `pynusmv.node.Node`)
representing the value being assigned to the requested symbol.
"""
return Node.from_ptr(_trace.Trace_step_get_value(
self.trace._ptr,
self._ptr,
symbol_node._ptr))
def test_make_nnf_boolean_wff(self):
load_from_string("""
MODULE main
VAR v : boolean;
w : boolean;
ASSIGN init(v) := TRUE;
next(v) := !v;
""")
with BmcSupport():
expr = Node.from_ptr(parse_ltl_spec("F G ( w <-> v )"))
wff = bmcutils.make_nnf_boolean_wff(expr)
self.assertEquals(" F ( G (w <-> v))", str(expr))
self.assertEquals(" F ( G ((!v | w) & (v | !w)))", str(wff))
self.assertEquals(Wff, type(wff))
def check(args, condition_text, observable):
"""
Performs the verification of the diagnosability of the condition represented
by `condition_text` and print its result to stdout.
:param args: the arguments that were given on the command line
:param condition_text: a string representing the diagnosability condition to
be verified in the format 'c1 ; c2'.
:param observable: the set of symbols considered observable in the context
of this diagnosability test
"""
try:
observable_vars = mk_observable_vars(observable)
diagnosability_condition = mk_specs_nodes(condition_text)
theta = Node.from_ptr(parse_simple_expression(args.initial_condition))
theta = make_nnf_boolean_wff(theta)
sigma1= Node.from_ptr(parse_ltl_spec(args.sigma1))
sigma1= make_nnf_boolean_wff(sigma1).to_node()
sigma2= Node.from_ptr(parse_ltl_spec(args.sigma2))
sigma2= make_nnf_boolean_wff(sigma2).to_node()
for k in range(args.bound+1):
result = verify_for_size_exactly_k(observable, observable_vars, diagnosability_condition, k, theta, sigma1, sigma2)
if "No Violation" != str(result):
print("-- {} is *NOT* diagnosable for length {}".format(diagnosability_condition, k))
print(result)
return
else:
print("-- No counter example at length {}".format(k))
print("-- No counter example found for executions of length <= {}".format(args.bound))
except Exception as e:
print("The specified condition contains a syntax error")
print(e)
def check(args, condition_text, observable):
"""
Performs the verification of the diagnosability of the condition represented
by `condition_text` and print its result to stdout.
:param args: the arguments that were given on the command line
:param condition_text: a string representing the diagnosability condition to
be verified in the format 'c1 ; c2'.
:param observable: the set of symbols considered observable in the context
of this diagnosability test
"""
try:
observable_vars = mk_observable_vars(observable)
diagnosability_condition = mk_specs_nodes(condition_text)
theta = Node.from_ptr(parse_simple_expression(args.initial_condition))
theta = make_nnf_boolean_wff(theta)
sigma1 = Node.from_ptr(parse_ltl_spec(args.sigma1))
sigma1 = make_nnf_boolean_wff(sigma1).to_node()
sigma2 = Node.from_ptr(parse_ltl_spec(args.sigma2))
sigma2 = make_nnf_boolean_wff(sigma2).to_node()
for k in range(args.bound + 1):
result = verify_for_size_exactly_k(
observable, observable_vars, diagnosability_condition, k, theta, sigma1, sigma2
)
if "No Violation" != str(result):
print("-- {} is *NOT* diagnosable for length {}".format(diagnosability_condition, k))
print(result)
return
print("-- No counter example found for executions of length <= {}".format(k))
except Exception as e:
print("The specified condition contains a syntax error")
print(e)
def test_is_loopback_when_frozen(self):
with BmcSupport():
sexp_fsm = master_bool_sexp_fsm()
be_fsm = master_be_fsm()
# empty trace
trace = Trace.create(
"Dummy example",
TraceType.COUNTER_EXAMPLE,
sexp_fsm.symbol_table,
sexp_fsm.symbols_list,
is_volatile=True,
)
step1 = trace.steps[1]
step2 = trace.append_step()
yes = Node.from_ptr(parse_simple_expression("TRUE"))
no = Node.from_ptr(parse_simple_expression("FALSE"))
v = be_fsm.encoding.by_name["v"].name
step1 += (v, yes)
step2 += (v, no)
trace.freeze()
step1.force_loopback()
self.assertTrue(step1.is_loopback)
self.assertFalse(step2.is_loopback)
step2.force_loopback()
self.assertTrue(step1.is_loopback)
# last step is never a loopback
self.assertFalse(step2.is_loopback)
trace.thaw()
self.assertFalse(step1.is_loopback)
self.assertFalse(step2.is_loopback)
def test_bounded_semantics_without_loop(self):
# parse the ltl property
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.bounded_semantics_without_loop(self.fsm, spec, bound=-1)
# verify that the generated expression corresponds to what is announced
no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
# globally w/o loop is false (this is just a test)
self.assertEqual(no_loop, Be.false(self.fsm.encoding.manager))
# an other more complex generation
spec = Node.from_ptr(parse_ltl_spec("F (y <= 7)"))
no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
#
# The generated expression is [[f]]^{0}_{k} so (! L_{k}) is not taken
# care of. And actually, NuSMV does not generate that part of the
# formula: it only enforce the loop condition when the semantics with
# loop is used
#
handcrafted = Be.false(self.fsm.encoding.manager)
y_le_seven = Wff(parse_ltl_spec("y <= 7")).to_boolean_wff().to_be(
self.fsm.encoding)
for time_x in reversed(
range(11)): # 11 because range 'eats' up the last step
handcrafted |= self.fsm.encoding.shift_to_time(y_le_seven, time_x)
#### debuging info #####
#print("noloop = {}".format(no_loop.to_cnf()))
#print("hancraft= {}".format(handcrafted.to_cnf()))
#print(self.fsm.encoding)
self.assertEqual(no_loop, handcrafted)
def test_assign_value__magicmethod__(self):
"""tests the behavior of assign and value"""
with BmcSupport():
sexp_fsm = master_bool_sexp_fsm()
be_fsm = master_be_fsm()
# empty trace
trace = Trace.create("Dummy example",
TraceType.COUNTER_EXAMPLE,
sexp_fsm.symbol_table,
sexp_fsm.symbols_list,
is_volatile=True)
step1 = trace.steps[1]
yes = Node.from_ptr(parse_simple_expression("TRUE"))
no = Node.from_ptr(parse_simple_expression("FALSE"))
v = be_fsm.encoding.by_name['v'].name
self.assertIsNone(step1.value[v])
step1 += (v, yes)
self.assertEqual(yes, step1.value[v])
step1 += (v, no)
self.assertEqual(no, step1.value[v])
def test_bounded_semantics(self):
# parse the ltl property
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.bounded_semantics(self.fsm, spec, bound=-1)
# it must raise exception when the bound and loop are not consistent
with self.assertRaises(ValueError):
ltlspec.bounded_semantics(self.fsm, spec, bound=5, loop=6)
# verify that the generated expression corresponds to what is announced
formula = ltlspec.bounded_semantics(self.fsm, spec, bound=10)
no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
all_loop = ltlspec.bounded_semantics_all_loops(self.fsm, spec, 10, 0)
self.assertEqual(formula, no_loop | all_loop)
def test_bounded_semantics(self):
# parse the ltl property
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.bounded_semantics(self.fsm, spec, bound=-1)
# it must raise exception when the bound and loop are not consistent
with self.assertRaises(ValueError):
ltlspec.bounded_semantics(self.fsm, spec, bound=5, loop=6)
# verify that the generated expression corresponds to what is announced
formula = ltlspec.bounded_semantics(self.fsm, spec, bound=10)
no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
all_loop= ltlspec.bounded_semantics_all_loops(self.fsm, spec, 10, 0)
self.assertEqual(formula, no_loop | all_loop)
def test_associative_array(self):
"""
This function tests the basic functions of the associative array proto
"""
h = Assoc(_u.new_assoc(), freeit=True)
a = Node.from_ptr(parse_simple_expression("a.car = 3"), freeit=False)
# __contains__
self.assertFalse(a in h)
# __setitem__
h[a] = a
self.assertTrue(a in h)
# __getitem__
self.assertEqual(h[a], a)
# __delitem__
del h[a]
self.assertFalse(a in h)
def test_generate_ltl_problem(self):
# parse the ltl property
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.generate_ltl_problem(self.fsm, spec, bound=-1)
# it must raise exception when the bound and loop are not consistent
with self.assertRaises(ValueError):
ltlspec.generate_ltl_problem(self.fsm, spec, bound=5, loop=6)
problem = ltlspec.generate_ltl_problem(self.fsm, spec, bound=10)
self.assertEqual("No counter example", self.do_verify(problem))
# verify that the generated problem corresponds to what is announced
model = BmcModel().path(10)
negspec = utils.make_negated_nnf_boolean_wff(spec)
formula = ltlspec.bounded_semantics(self.fsm, negspec, bound=10)
self.assertEqual(problem, model & formula)
def test_generate_ltl_problem(self):
# parse the ltl property
spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
# it must raise exception when the bound is not feasible
with self.assertRaises(ValueError):
ltlspec.generate_ltl_problem(self.fsm, spec, bound=-1)
# it must raise exception when the bound and loop are not consistent
with self.assertRaises(ValueError):
ltlspec.generate_ltl_problem(self.fsm, spec, bound=5, loop=6)
problem = ltlspec.generate_ltl_problem(self.fsm, spec, bound=10)
self.assertEqual("No counter example", self.do_verify(problem))
# verify that the generated problem corresponds to what is announced
model = BmcModel().path(10)
negspec = utils.make_negated_nnf_boolean_wff(spec)
formula = ltlspec.bounded_semantics(self.fsm, negspec, bound=10)
self.assertEqual(problem, model & formula)
def test_concat(self):
with BmcSupport():
sexp_fsm = master_bool_sexp_fsm()
be_fsm = master_be_fsm()
trace = Trace.create(
"Dummy example",
TraceType.COUNTER_EXAMPLE,
sexp_fsm.symbol_table,
sexp_fsm.symbols_list,
is_volatile=True,
)
spec = Node.from_ptr(parse_ltl_spec("F (w <-> v)"))
bound = 2
problem = generate_ltl_problem(be_fsm, spec, bound=bound) # .inline(True)
cnf = problem.to_cnf()
solver = SatSolverFactory.create()
solver += cnf
solver.polarity(cnf, Polarity.POSITIVE)
solver.solve()
other = generate_counter_example(be_fsm, problem, solver, bound)
trace.concat(other)
self.assertEquals(-1, trace.id)
self.assertFalse(trace.is_registered)
self.assertEquals("Dummy example", trace.description)
self.assertEquals(TraceType.COUNTER_EXAMPLE, trace.type)
self.assertTrue(trace.is_volatile)
self.assertEquals(2, trace.length)
self.assertEquals(2, len(trace))
self.assertFalse(trace.is_empty)
self.assertFalse(trace.is_frozen)
self.assertTrue(trace.is_thawed)
