'test_query': 0,
'state_count': 0,
'error_count': 0,
'errors': set()
},
log_path=logdir.joinpath(f'{problem}_{now}_afl_wtraces.log'),
write_on_change={'state_count', 'error_count'})
sul = RERSSOConnector(path)
afl_dir = f'/home/tom/projects/lstar/experiments/learningfuzzing/{problemset}/{problem}'
bin_path = f'/home/tom/projects/lstar/experiments/learningfuzzing/{problemset}/{problem}/{problem}'
eqc = StackedChecker(
AFLEquivalenceCheckerV2(sul, afl_dir, bin_path, feedback='w_traces'),
SmartWmethodEquivalenceCheckerV2(sul,
horizon=horizon,
stop_on={'invalid_input'},
stop_on_startswith={'error'}))
# Set up the teacher, with the system under learning and the equivalence checker
teacher = Teacher(sul, eqc)
# Set up the learner who only talks to the teacher
learner = TTTMealyLearner(teacher)
# Get the learners hypothesis
hyp = learner.run(show_intermediate=False,
render_options={'ignore_self_edges': ['error', 'invalid']},
on_hypothesis=savehypothesis(
f'hypotheses/afl_plain/{problem}', f'{problem}'))
# SmartWmethodEquivalenceCheckerV2(sul,
# horizon=horizon,
# stop_on={'invalid_input'},
# stop_on_startswith={'error'})
)
# Set up the teacher, with the system under learning and the equivalence checker
teacher = Teacher(sul, eqc)
# Set up the learner who only talks to the teacher
learner = TTTMealyLearner(teacher)
# Get the learners hypothesis
hyp = learner.run(
show_intermediate=False,
on_hypothesis=savehypothesis(f'hypotheses/{problemset}/{problem}', f'{problem}')
)
end_learning = datetime.now()
# hyp.render_graph()
nusmv = NuSMVUtils(constrpath, mappingpath)
ltl_answers = nusmv.run_ltl_check(hyp)
if 'Training' in problemset or problemset == 'SeqLtlRers2019':
scores.append(check_result(ltl_answers, solutionspath))
Path(f'results/{problemset}').mkdir(exist_ok=True, parents=True)
SmartWmethodEquivalenceCheckerV2(sul,
horizon=horizon,
stop_on={'invalid_input'},
stop_on_startswith={'error'}),
)
# Set up the teacher, with the system under learning and the equivalence checker
teacher = Teacher(sul, eqc)
# Set up the learner who only talks to the teacher
learner = TTTMealyLearner(teacher)
# Get the learners hypothesis
hyp = learner.run(show_intermediate=False,
render_options={'ignore_self_edges': ['error', 'invalid']},
on_hypothesis=savehypothesis(f'hypotheses/ltl/{problem}',
f'{problem}'))
nusmv = NuSMVUtils(constrpath, mappingpath)
result = nusmv.run_ltl_check(hyp)
print(result)
#
# mealy_lines = mealy2nusmv_withintermediate(hyp)
# ltl_lines = rersltl2smv_withintermediate(constrpath, mappingpath)
#
# smvdir = Path(f'./smv/{problemset}')
# smvdir.mkdir(parents=True, exist_ok=True)
#
# with open(smvdir.joinpath(f'{problem}.smv'), 'w') as file:
# fuzzer_path=fuzzer_path,
# eqchecktype=EQCheckType.BOTH,
# enable_dtraces=False,
# minimize=False)
# eqc = SmartWmethodEquivalenceCheckerV4(sul,
# horizon=13,
# stop_on={'invalid_input'},
# stop_on_startswith={'error'},
# order_type='shortest first')
eqc = SmartWmethodEquivalenceCheckerV2(sul,
horizon=13,
stop_on={'invalid_input'},
stop_on_startswith={'error'})
#order_type='shortest first')
# Set up the teacher, with the system under learning and the equivalence checker
teacher = Teacher(sul, eqc)
# Set up the learner who only talks to the teacher
learner = TTTMealyLearner(teacher)
# Get the learners hypothesis
hyp = learner.run(show_intermediate=False,
render_options={'ignore_self_edges': ['error', 'invalid']},
on_hypothesis=savehypothesis(f'hypotheses/{problem}_wmethod',
f'{problem}'))
hyp.render_graph(render_options={'ignore_self_edges': ['error', 'invalid']})
check_result(
hyp,
f'../../rers/{problemset}/{problem}/reachability-solution-{problem}.csv')
def stack(*args):
def chained(hypothesis):
for function in args:
function(hypothesis)
return chained
# Get the learners hypothesis
hyp = learner.run(
show_intermediate=False,
render_options={'ignore_self_edges': ['error', 'invalid']},
on_hypothesis=stack(
savehypothesis(f'{prefix}/hypotheses/{problemset}/{problem}',
f'{problem}'),
lambda x: check_result(
x,
f'../../rers/TrainingSeqReachRers2019/{problem}/reachability-solution-{problem}.csv'
)))
print(
"SUCCES",
check_result(
hyp,
f'../../rers/TrainingSeqReachRers2019/{problem}/reachability-solution-{problem}.csv'
))
#hyp.render_graph(render_options={'ignore_self_edges': ['error', 'invalid']})
'errors': set()
},
log_path=logdir.joinpath(f'{problem}_{now}_reach.log'),
write_on_change={'state_count', 'error_count'})
sul = RERSSOConnector(path)
afl_dir = f'{args.afl_dir}/{problemset}/{problem}'
bin_path = f'{args.afl_dir}/{problemset}/{problem}/{problem}'
eqc = StackedChecker(
AFLEquivalenceCheckerV2(sul,
afl_dir,
bin_path,
eqchecktype=EQCheckType.BOTH),
SmartWmethodEquivalenceCheckerV2(sul,
horizon=horizon,
stop_on={'invalid_input'},
stop_on_startswith={'error'}))
# Set up the teacher, with the system under learning and the equivalence checker
teacher = Teacher(sul, eqc)
# Set up the learner who only talks to the teacher
learner = TTTMealyLearner(teacher)
# Get the learners hypothesis
hyp = learner.run(show_intermediate=False,
render_options={'ignore_self_edges': ['error', 'invalid']},
on_hypothesis=savehypothesis(f'hypotheses/reach/{problem}',
f'{problem}'))
