def test_bmc_setup(self):
# pre conditions not satisfied
# model must be loaded
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# vars need to be encoded
load(self.model())
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# boolean model must be compiled out of the sexp
flatten_hierarchy()
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# hierarchy must be flattened (actually, this is a requirement for the
# boolean model too)
encode_variables()
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# may not be called 2 times
build_boolean_model()
with self.assertRaises(NuSMVBmcAlreadyInitializedError):
bmcglob.bmc_setup()
bmcglob.bmc_setup()
# even if the force flag is on (that's COI related)
with self.assertRaises(NuSMVBmcAlreadyInitializedError):
bmcglob.bmc_setup(force=True)
bmcglob.bmc_exit()
def process(path_to, model, formula=None, depths=range(10), flags=IDLE):
'''
Initializes PyNuSMV and loads the model, then proceeds to the bulk of the
analysis. See `analyze_one` and `analyze_all` for further details about
what is done.
By default, this analysis generates no output. However the following flags
can be customized to generate derived artifacts.
+ 'dimacs = True' will produce a *.cnf file containing the dimacs
representation of the problem
+ 'structure = True' will produce a *.png file visually representing the
variable graph.
+ 'clouds = True' will produce a wordcloud (*.png file) per analyzed
community to show the semantic information that occurs the most often
in that community.
+ 'stats = True' will produce a csv file containing all the raw
statistical data alongside with two charts plotting the evolution of
the #communities and modulatity over time
'''
with init_nusmv():
load(core.merge_model_text(path_to, model + ".smv"))
with BmcSupport():
analyze_all(model, formula, depths, flags)
def test_bmc_setup(self):
# pre conditions not satisfied
# model must be loaded
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# vars need to be encoded
load(self.model())
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# boolean model must be compiled out of the sexp
flatten_hierarchy()
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# hierarchy must be flattened (actually, this is a requirement for the
# boolean model too)
encode_variables()
with self.assertRaises(NuSMVNeedBooleanModelError):
bmcglob.bmc_setup()
# may not be called 2 times
build_boolean_model()
with self.assertRaises(NuSMVBmcAlreadyInitializedError):
bmcglob.bmc_setup()
bmcglob.bmc_setup()
# even if the force flag is on (that's COI related)
with self.assertRaises(NuSMVBmcAlreadyInitializedError):
bmcglob.bmc_setup(force=True)
bmcglob.bmc_exit()
def test_mc_ltl_true(self):
# Initialize the model
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model()
fsm = glob.prop_database().master.bddFsm
spec = prop.Spec(parser.parse_ltl_spec("G admin = none"))
self.assertEqual(mc.check_ltl_spec(spec), False)
def test_load_from_string(self):
main = """
MODULE main
VAR state : boolean;
INIT state
TRANS next(state) = !state
"""
glob.load(main)
def setUp(self):
init_nusmv()
glob.load(
tests.current_directory(__file__) +
"/models/flipflops_explicit_relation.smv")
go_bmc()
self._fsm = BeFsm.global_master_instance()
self._manager = self._fsm.encoding.manager
def test_ex(self):
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model()
fsm = glob.prop_database().master.bddFsm
alice = mc.eval_simple_expression(fsm, "admin = alice")
spec = prop.Spec(parser.parse_ctl_spec("EX admin = alice"))
exalice = mc.eval_ctl_spec(fsm, spec)
self.assertEqual(mc.ex(fsm, alice), exalice)
def test_load_from_string_syntax_errors(self):
main = """
MODULE main
VAR state : boolean
INIT state
TRANS next(state) = !state
"""
with self.assertRaises(NuSMVParsingError):
glob.load(main)
def test_build_master_be_fsm(self):
load(self.model())
flatten_hierarchy()
encode_variables()
build_boolean_model()
bmcglob.bmc_setup()
# may not provoke C assert failures
bmcglob.build_master_be_fsm()
bmcglob.bmc_exit()
def test_force_reordering(self):
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model(variables_ordering="tests/pynusmv/models/admin.ord")
fsm = glob.prop_database().master.bddFsm
self.assertTupleEqual(("admin", "state"),
fsm.bddEnc.get_variables_ordering())
reorder(fsm.bddEnc.DDmanager)
self.assertTupleEqual(("state", "admin"),
fsm.bddEnc.get_variables_ordering())
def setUp(self):
init_nusmv()
glob.load(self.model())
glob.flatten_hierarchy()
glob.encode_variables() # does it for BDD
self.go_bmc()
pd = _prop.PropPkg_get_prop_database()
fsm = _prop.PropDb_master_get_be_fsm(pd)
self._TEST = _be.BeFsm_get_fairness_list(fsm)
def test_force_reordering(self):
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model(variables_ordering="tests/pynusmv/models/admin.ord")
fsm = glob.prop_database().master.bddFsm
self.assertTupleEqual(("admin", "state"),
fsm.bddEnc.get_variables_ordering())
reorder(fsm.bddEnc.DDmanager)
self.assertTupleEqual(("state", "admin"),
fsm.bddEnc.get_variables_ordering())
def test_master_be_fsm(self):
load(self.model())
flatten_hierarchy()
encode_variables()
build_boolean_model()
bmcglob.bmc_setup()
# may not provoke C assert failures
bmcglob.build_master_be_fsm()
self.assertEqual(bmcglob.master_be_fsm(), BeFsm.global_master_instance())
bmcglob.bmc_exit()
def setUp(self):
init_nusmv()
glob.load(self.model())
glob.flatten_hierarchy()
glob.encode_variables() # does it for BDD
self.go_bmc()
pd = _prop.PropPkg_get_prop_database()
fsm= _prop.PropDb_master_get_be_fsm(pd)
self._TEST = _be.BeFsm_get_fairness_list(fsm)
def test_build_master_be_fsm(self):
load(self.model())
flatten_hierarchy()
encode_variables()
build_boolean_model()
bmcglob.bmc_setup()
# may not provoke C assert failures
bmcglob.build_master_be_fsm()
bmcglob.bmc_exit()
def test_master_be_fsm(self):
load(self.model())
flatten_hierarchy()
encode_variables()
build_boolean_model()
bmcglob.bmc_setup()
# may not provoke C assert failures
bmcglob.build_master_be_fsm()
self.assertEqual(bmcglob.master_be_fsm(),
BeFsm.global_master_instance())
bmcglob.bmc_exit()
def test_mc_explain_ltl_true(self):
# Initialize the model
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model()
spec = prop.Spec(
parser.parse_ltl_spec("(F admin = alice) | (F admin = bob)"))
result, explanation = mc.check_explain_ltl_spec(spec)
self.assertTrue(result)
self.assertIsNone(explanation)
def test_bmcSupport(self):
# model MUST be loaded
with self.assertRaises(NuSMVNoReadModelError):
with bmcglob.BmcSupport():
# may not provoke any error
pass
load(self.model())
with bmcglob.BmcSupport():
# may not provoke any error
pass
def test_au(self):
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model()
fsm = glob.prop_database().master.bddFsm
none = mc.eval_simple_expression(fsm, "admin = none")
alice = mc.eval_simple_expression(fsm, "admin = alice")
spec = prop.Spec(
parser.parse_ctl_spec("A[admin = none U admin = alice]"))
aunonealice = mc.eval_ctl_spec(fsm, spec)
self.assertEqual(mc.au(fsm, none, alice), aunonealice)
def test_bmcSupport(self):
# model MUST be loaded
with self.assertRaises(NuSMVNoReadModelError):
with bmcglob.BmcSupport():
# may not provoke any error
pass
load(self.model())
with bmcglob.BmcSupport():
# may not provoke any error
pass
def test_eg(self):
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model()
fsm = glob.prop_database().master.bddFsm
alice = mc.eval_simple_expression(fsm, "admin = alice")
spec = prop.Spec(parser.parse_ctl_spec("EG admin = alice"))
egalice = mc.eval_ctl_spec(fsm, spec)
self.assertEqual(mc.eg(fsm, alice), egalice)
self.assertEqual(
egalice,
fixpoint(lambda Z: alice & fsm.pre(Z), BDD.true())
& fsm.reachable_states)
def test_change_trans_of_flat(self):
glob.load(*self.counters())
glob.flatten_hierarchy()
flat = glob.flat_hierarchy()
self.assertIsNotNone(flat)
trans = flat.trans
choose_run = node.Expression.from_string("run = rc1")
flat.trans = flat.trans & choose_run
glob.compute_model()
fsm = glob.prop_database().master.bddFsm
self.assertEqual(fsm.count_states(fsm.reachable_states), 3)
def test_change_trans_of_flat(self):
glob.load(*self.counters())
glob.flatten_hierarchy()
flat = glob.flat_hierarchy()
self.assertIsNotNone(flat)
trans = flat.trans
choose_run = node.Expression.from_string("run = rc1")
flat.trans = flat.trans & choose_run
glob.compute_model()
fsm = glob.prop_database().master.bddFsm
self.assertEqual(fsm.count_states(fsm.reachable_states), 3)
def main():
args = arguments()
with init_nusmv():
load(args.model)
if args.verbose:
with open(args.model) as f:
print(f.read())
with BmcSupport():
if args.spec is not None:
check(args.spec, args)
else:
print("Enter LTL properties, one per line:")
for line in sys.stdin:
check(line, args)
def test_go_bmc(self):
# pre conditions not satisfied
# model must be loaded
with self.assertRaises(NuSMVNoReadModelError):
bmcglob.go_bmc()
# vars need to be encoded
load(self.model())
# it doesn't hurt to call it more than once
bmcglob.go_bmc()
bmcglob.go_bmc()
# unless the force flag is on
bmcglob.go_bmc(force=True)
bmcglob.bmc_exit()
def test_mc_explain_ltl_false(self):
# Initialize the model
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model()
spec = prop.Spec(parser.parse_ltl_spec("G admin = none"))
result, explanation = mc.check_explain_ltl_spec(spec)
self.assertFalse(result)
self.assertIsNotNone(explanation)
#print(explanation[0])
#for inputs, state in zip(explanation[1::2], explanation[2::2]):
# print(inputs)
# print(state)
self.assertTrue(
any(state["admin"] != "none" for state in explanation[::2]))
def test_go_bmc(self):
# pre conditions not satisfied
# model must be loaded
with self.assertRaises(NuSMVNoReadModelError):
bmcglob.go_bmc()
# vars need to be encoded
load(self.model())
# it doesn't hurt to call it more than once
bmcglob.go_bmc()
bmcglob.go_bmc()
# unless the force flag is on
bmcglob.go_bmc(force=True)
bmcglob.bmc_exit()
def test_access_flat_hierarchy(self):
glob.load(*self.counters())
glob.compute_model()
flat = glob.flat_hierarchy()
symb_table = glob.symb_table()
self.assertIsNotNone(flat.init)
self.assertIsNotNone(flat.trans)
self.assertIsNone(flat.invar)
self.assertIsNone(flat.justice)
self.assertIsNone(flat.compassion)
variables = flat.variables
for variable in variables:
var_type = symb_table.get_variable_type(variable)
self.assertEqual(nssymb_table.SymbType_get_tag(var_type),
nssymb_table.SYMB_TYPE_ENUM)
def test_access_flat_hierarchy(self):
glob.load(*self.counters())
glob.compute_model()
flat = glob.flat_hierarchy()
symb_table = glob.symb_table()
self.assertIsNotNone(flat.init)
self.assertIsNotNone(flat.trans)
self.assertIsNone(flat.invar)
self.assertIsNone(flat.justice)
self.assertIsNone(flat.compassion)
variables = flat.variables
for variable in variables:
var_type = symb_table.get_variable_type(variable)
self.assertEqual(nssymb_table.SymbType_get_tag(var_type),
nssymb_table.SYMB_TYPE_ENUM)
def proceed(args):
"""Actually proceeds to the verification"""
with init_nusmv():
load(args.model)
with BmcSupport():
observable = mk_observable_names(args)
if not args.quiet:
with open(args.model) as m:
model = m.read()
print_greeting(model, observable)
if args.spec is not None:
check(args, args.spec, observable)
else:
print("*"*80)
print("* DIAGNOSABILITY TESTS")
print("*"*80)
print("Enter diagnosability condition, one per line in the format: 'c1 ; c2'")
for line in sys.stdin:
check(args, line, observable)
def proceed(args):
"""Actually proceeds to the verification"""
with init_nusmv():
load(args.model)
with BmcSupport():
observable = mk_observable_names(args)
if not args.quiet:
with open(args.model) as m:
model = m.read()
print_greeting(model, observable)
if args.spec is not None:
check(args, args.spec, observable)
else:
print("*" * 80)
print("* DIAGNOSABILITY TESTS")
print("*" * 80)
print("Enter diagnosability condition, one per line in the format: 'c1 ; c2'")
for line in sys.stdin:
check(args, line, observable)
def setUp(self):
init_nusmv()
glob.load(tests.current_directory(__file__) + "/models/flipflops_explicit_relation.smv")
go_bmc()
self._fsm = BeFsm.global_master_instance()
self._manager = self._fsm.encoding.manager
def setUp(self):
init_nusmv()
load(self.model())
def cli(model_path, query, order):
"""Solve QUERY that belongs to fragment CTLQx for model in MODEL_PATH."""
try:
# Parse `query` and transform it in NNF.
ast = negation_normal_form(parse_ctlq(query))
# Check that `query` belongs to fragment CTLQx.
if not check_ctlqx(ast):
click.echo('Error: {query} does not belong to CTLQx'
.format(query=query))
# Quit PyTLQ.
sys.exit()
# Initialize NuSMV.
with init_nusmv():
# Load model from `model_path`.
load(model_path)
# Enable dynamic reordering of the variables.
enable_dynamic_reordering()
# Check if an order file is given.
if order:
# Build model with pre-calculated variable ordering.
compute_model(variables_ordering=order)
else:
# Build model.
compute_model()
# Retrieve FSM of the model.
fsm = prop_database().master.bddFsm
# Solve `query` in `fsm`.
solution = solve_ctlqx(fsm, ast)
# Display solution.
click.echo('Solution states:')
if not solution:
click.echo('No solution')
# Quit PyTLQ.
sys.exit()
elif solution.is_false():
click.echo('False')
# Quit PyTLQ.
sys.exit()
else:
size = fsm.count_states(solution)
if size > 100:
if click.confirm('The number of states is too large'
' ({size}). Do you still want to print'
' them?'.format(size=size)):
pprint(bdd_to_set(fsm, solution))
else:
pprint(bdd_to_set(fsm, solution))
# Ask for further manipulations.
while True:
command = click.prompt('\nWhat do you want to do?'
'\n 1. Project the solution on a'
' subset of the variables'
'\n 2. Simplify the solution according'
' to Chan\'s approximate conjunctive'
' decomposition'
'\n 3. Quit PyTLQ'
'\nYour choice',
type=click.IntRange(1, 3), default=3)
# Check if solution must be projected or simplified.
if command == 1 or command == 2:
# Gather more information.
click.echo('')
if command == 2:
maximum = click.prompt('Please enter the maximum'
' number of variables that must'
' appear in the conjuncts of'
' the simplification', type=int,
default=1)
variables = click.prompt('Please enter the list of'
' variables of interest,'
' separated by commas', type=str,
default='all the variables')
# Format `variables`.
if variables == 'all the variables':
variables = None
else:
variables = variables.replace(" ", "").split(',')
if command == 1:
# Project solution and display projection.
click.echo('\nProjection:')
click.echo(project(fsm, solution, variables))
else:
# Simplify solution and display simplification.
click.echo('\nApproximate conjunctive decomposition:')
click.echo(simplify(fsm, solution, maximum, variables))
# No further manipulations are needed.
else:
break
except Exception as error:
click.echo('Error: {msg}'.format(msg=error))
def setUp(self):
init_nusmv()
glob.load(self.model())
go_bmc()
self.enc = master_be_fsm().encoding
def test_cdr(self):
glob.load(*self.counters())
glob.compute_model()
spec = node.Node.from_ptr(parse_ctl_spec("A [x U y]"))
self.assertEqual(type(spec.cdr), node.Atom)
self.assertEqual(str(spec.cdr), "y")
def setUp(self):
init_nusmv()
load(self.model())
def load_admin_model(self):
glob.load("tests/pynusmv/models/admin.smv")
glob.compute_model()
def setUp(self):
init_nusmv()
load(self.model())
go_bmc()
self.fsm = BeFsm.global_master_instance()
def setUp(self):
init_nusmv()
load(self.model())
go_bmc()
self.fsm = BeFsm.global_master_instance()
def cli(model_path, query, order):
"""Solve QUERY that belongs to fragment CTLQx for model in MODEL_PATH."""
try:
# Parse `query` and transform it in NNF.
ast = negation_normal_form(parse_ctlq(query))
# Check that `query` belongs to fragment CTLQx.
if not check_ctlqx(ast):
click.echo("Error: {query} does not belong to CTLQx".format(query=query))
# Quit PyTLQ.
sys.exit()
# Initialize NuSMV.
with init_nusmv():
# Load model from `model_path`.
load(model_path)
# Enable dynamic reordering of the variables.
enable_dynamic_reordering()
# Check if an order file is given.
if order:
# Build model with pre-calculated variable ordering.
compute_model(variables_ordering=order)
else:
# Build model.
compute_model()
# Retrieve FSM of the model.
fsm = prop_database().master.bddFsm
# Solve `query` in `fsm`.
solution = solve_ctlqx(fsm, ast)
# Display solution.
click.echo("Solution states:")
if not solution:
click.echo("No solution")
# Quit PyTLQ.
sys.exit()
elif solution.is_false():
click.echo("False")
# Quit PyTLQ.
sys.exit()
else:
size = fsm.count_states(solution)
if size > 100:
if click.confirm(
"The number of states is too large"
" ({size}). Do you still want to print"
" them?".format(size=size)
):
pprint(bdd_to_set(fsm, solution))
else:
pprint(bdd_to_set(fsm, solution))
# Ask for further manipulations.
while True:
command = click.prompt(
"\nWhat do you want to do?"
"\n 1. Project the solution on a"
" subset of the variables"
"\n 2. Simplify the solution according"
" to Chan's approximate conjunctive"
" decomposition"
"\n 3. Quit PyTLQ"
"\nYour choice",
type=click.IntRange(1, 3),
default=3,
)
# Check if solution must be projected or simplified.
if command == 1 or command == 2:
# Gather more information.
click.echo("")
if command == 2:
maximum = click.prompt(
"Please enter the maximum"
" number of variables that must"
" appear in the conjuncts of"
" the simplification",
type=int,
default=1,
)
variables = click.prompt(
"Please enter the list of" " variables of interest," " separated by commas",
type=str,
default="all the variables",
)
# Format `variables`.
if variables == "all the variables":
variables = None
else:
variables = variables.replace(" ", "").split(",")
if command == 1:
# Project solution and display projection.
click.echo("\nProjection:")
click.echo(project(fsm, solution, variables))
else:
# Simplify solution and display simplification.
click.echo("\nApproximate conjunctive decomposition:")
click.echo(simplify(fsm, solution, maximum, variables))
# No further manipulations are needed.
else:
break
except Exception as error:
click.echo("Error: {msg}".format(msg=error))
print("-- No problem at length {}".format(i))
else:
print(" 'Problem {}' ; {}".format(i, end-start))
return ("Ok", bound, None)
def check(formula, args):
parsed_fml = Node.from_ptr(parse_ltl_spec(formula.strip()))
status,length,trace = check_ltl(parsed_fml, args.bound, args.dry_run)
if status != 'Ok':
print("-- {} for length {}".format(status, length))
print(trace)
if __name__ == "__main__":
args = arguments()
with init_nusmv():
load(args.model)
if args.verbose:
with open(args.model) as f:
print(f.read())
with BmcSupport():
if args.spec is not None:
check(args.spec, args)
else:
print("Enter LTL properties, one per line:")
for line in sys.stdin:
check(line, args)
def test_cdr(self):
glob.load(*self.counters())
glob.compute_model()
spec = node.Node.from_ptr(parse_ctl_spec("A [x U y]"))
self.assertEqual(type(spec.cdr), node.Atom)
self.assertEqual(str(spec.cdr), "y")
