def compute_J(protocol, valuation, disabled, F, mem, graph, vertices):
key = (valuation, frozenset(disabled))
if key in mem:
return mem[key]
newM = set()
M = set()
sF = set(F)
distance = shortest_distance(graph, directed=True)
while not (len(newM) == len(sF)):
newM = nextH(newM, sF.difference(newM), distance, vertices)
M = newM
stable = (len(M) == 0)
while not stable:
to_remove = set()
for pair in M: # AB
constraints = []
for t in protocol.transitions:
if (t.post == pair):
constraints.append(([], [], t.pre))
elif len(set(pair) & t.postset) == 1:
p = tuple(set(pair) & t.postset)[0] # E
q = pair.other(p) # F
q_ = t.post.other(p) # G
if (q_ != q): # G != F
if p != q: # E != F
constraints.append(([Var(q)], [Var(p)], t.pre))
elif p not in t.pre: # E = F and E not in AB
constraints.append(([Var(p, True)], [], t.pre))
formula = Formula(valuation, disabled | M)
if not formula.tautology_check(constraints):
to_remove.add(pair)
if len(to_remove) > 0:
M -= to_remove
else:
stable = True
if len(M) > 0:
break
mem[key] = M
return M
def compute_J(protocol, valuation, disabled, F, mem):
key = (valuation, frozenset(disabled))
if key in mem:
return mem[key]
M = set(F)
stable = (len(M) == 0)
while not stable:
to_remove = set()
for pair in M: # AB
constraints = []
for t in protocol.transitions:
if (t.post == pair):
constraints.append(([], [], t.pre))
elif len(set(pair) & t.postset) == 1:
p = tuple(set(pair) & t.postset)[0] # E
q = pair.other(p) # F
q_ = t.post.other(p) # G
if (q_ != q): # G != F
if p != q: # E != F
constraints.append(([Var(q)], [Var(p)], t.pre))
elif p not in t.pre: # E = F and E not in AB
constraints.append(([Var(p, True)], [], t.pre))
formula = Formula(valuation, disabled | M)
if not formula.tautology_check(constraints):
to_remove.add(pair)
if len(to_remove) > 0:
M -= to_remove
else:
stable = True
mem[key] = M
return M
