def is_stable_or_dead(protocol, valuation, disabled):
# Dead?
dead = True
for t in protocol.transitions:
p, q = tuple(t.pre)
if (not t.silent() and (t.pre not in disabled)
and (valuation[Var(p)] is not False)
and (valuation[Var(q)] is not False)):
dead = False
break
if dead:
return True
# Stable?
V = protocol.states - valuation.absent_states()
out = {protocol.output(q) for q in V}
if len(out) > 1:
return False
else:
x = out.pop()
R = set()
for t in protocol.transitions:
for q in t.post:
if protocol.output(q) != x:
R.add(t.pre)
formula = Formula(valuation, disabled)
return formula.implies_all_absent_tautology_check(R)
def is_very_fast(protocol, valuation, disabled):
graph, vertices, edges = transformation_graph(protocol, valuation,
disabled)
components, _, is_bottom = label_components(graph, attractors=True)
U = {q for q in vertices if not is_bottom[components[vertices[q]]]}
formula = Formula(valuation, disabled)
for t in protocol.transitions:
p, q = tuple(t.pre)
p_, q_ = tuple(t.post)
if (p in vertices and q in vertices and p_ in vertices
and q_ in vertices and len({p, q, p_, q_} & U) > 0):
if ((components[vertices[p]] != components[vertices[p_]])
and (components[vertices[p]] != components[vertices[q_]])
and (components[vertices[q]] != components[vertices[p_]])
and (components[vertices[q]] != components[vertices[q_]])):
continue
elif formula.implies_all_absent_tautology_check({t.pre}):
continue
else:
return False
return True
