def _remap_model_bwd(self, vars, model, k):
retmodel = dict()
for var in vars:
for t in range(k+1):
if TS.get_ptimed(var, k-t) in model:
retmodel[TS.get_timed(var, t)] = model[TS.get_ptimed(var, k-t)]
return retmodel
def _get_param_assignments(self, model, time, parameters, monotonic=True):
p_ass = []
fwd = False
for p in parameters:
p_time = model[TS.get_ptimed(p, 0)]
if p.symbol_type() == BOOL:
if monotonic:
if p_time == TRUE():
p_ass.append(p)
else:
p_ass.append(p if p_time == TRUE() else Not(p))
else:
p_ass.append(EqualsOrIff(p, p_time))
p_ass = And(p_ass)
self.region = simplify(Or(self.region, p_ass))
if self.models is None:
self.models = []
self.models.append((model, time))
Logger.msg("+", 0, not (Logger.level(1)))
self.cs_count += 1
Logger.log(
"Found assignment \"%s\"" % (p_ass.serialize(threshold=100)), 1)
return (p_ass, False)
def _get_param_assignments(self, model, time, parameters, monotonic=True):
p_ass = []
fwd = False
for p in parameters:
# search the trace for any enabled faults
ever_true = False
for t in range(time + 1):
p_time = model[TS.get_ptimed(p, 0)]
if p.symbol_type() == BOOL:
if p_time == TRUE():
ever_true = True
break
if ever_true:
p_ass.append(p)
elif not monotonic:
p_ass.append(EqualsOrIff(p, FALSE()))
p_ass = And(p_ass)
self.region = simplify(Or(self.region, p_ass))
if self.models is None:
self.models = []
self.models.append((model, time))
Logger.msg("+", 0, not (Logger.level(1)))
self.cs_count += 1
Logger.log(
"Found assignment \"%s\"" % (p_ass.serialize(threshold=100)), 1)
return (p_ass, False)
def _remap_model_zz(self, vars, model, k):
retmodel = dict([el for el in dict(model).items() if not TS.is_ptimed(el[0])])
for var in vars:
for t in range(int(k/2)+1, k+1, 1):
retmodel[TS.get_timed(var, t)] = model[TS.get_ptimed(var, k-t)]
return retmodel
def _remap_model_zz(self, vars, model, k):
retmodel = dict(model)
for var in vars:
for t in range(int(k / 2) + 1, k + 1, 1):
retmodel[TS.get_timed(var,
t)] = model[TS.get_ptimed(var, k - t)]
return retmodel
