def upre_bdd(self,
dst_states_bdd,
env_strat=None,
get_strat=False,
use_trans=False):
"""
UPRE = EXu.AXc.EL' : T(L,Xu,Xc,L') ^ dst(L') [^St(L,Xu)]
"""
# take a transition step backwards
# TECH NOTE: the restrict_fun=~dst... works ONLY because I will use the
# result and take the union with dst_states afterwards...
p_bdd = self.substitute_latches_next(dst_states_bdd,
restrict_fun=~dst_states_bdd,
use_trans=use_trans)
# use the given strategy
if env_strat is not None:
p_bdd &= env_strat
# there is an uncontrollable action such that for all contro...
temp_bdd = p_bdd.univ_abstract(
BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.iterate_controllable_inputs())))
p_bdd = temp_bdd.exist_abstract(
BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.iterate_uncontrollable_inputs())))
# prepare the output
if get_strat:
return temp_bdd
else:
return p_bdd
def upre_bdd(self, dst_states_bdd, env_strat=None, get_strat=False,
use_trans=False):
"""
UPRE = EXu.AXc.EL' : T(L,Xu,Xc,L') ^ dst(L') [^St(L,Xu)]
"""
# take a transition step backwards
# TECH NOTE: the restrict_fun=~dst... works ONLY because I will use the
# result and take the union with dst_states afterwards...
p_bdd = self.substitute_latches_next(
dst_states_bdd,
restrict_fun=~dst_states_bdd,
use_trans=use_trans)
# use the given strategy
if env_strat is not None:
p_bdd &= env_strat
# there is an uncontrollable action such that for all contro...
temp_bdd = p_bdd.univ_abstract(
BDD.make_cube(imap(funcomp(BDD, symbol_lit),
self.iterate_controllable_inputs())))
p_bdd = temp_bdd.exist_abstract(
BDD.make_cube(imap(funcomp(BDD, symbol_lit),
self.iterate_uncontrollable_inputs())))
# prepare the output
if get_strat:
return temp_bdd
else:
return p_bdd
def __init__(self, aig):
self.aig = aig
self.uinputs = [x.lit for x in
self.aig.iterate_uncontrollable_inputs()]
self.latches = [x.lit for x in self.aig.iterate_latches()]
self.latch_cube = BDD.make_cube(imap(funcomp(BDD,
symbol_lit),
self.aig.iterate_latches()))
self.platch_cube = BDD.make_cube(imap(funcomp(BDD,
self.aig.get_primed_var,
symbol_lit),
self.aig.iterate_latches()))
self.cinputs_cube = BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.aig.iterate_controllable_inputs()))
self.pcinputs_cube = self.aig.prime_all_inputs_in_bdd(
self.cinputs_cube)
self.uinputs_cube = BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.aig.iterate_uncontrollable_inputs()))
self.init_state_bdd = self.aig.init_state_bdd()
self.error_bdd = self.aig.lit2bdd(self.aig.error_fake_latch.lit)
self.Venv = dict()
self.Venv[self.init_state_bdd] = True
self.succ_cache = dict()
def over_post_bdd(self, src_states_bdd, sys_strat=None):
""" Over-approximated version of concrete post which can be done even
without the transition relation """
strat = BDD.true()
if sys_strat is not None:
strat &= sys_strat
# to do this, we use an over-simplified transition relation, EXu,Xc
b = BDD.true()
for x in self.iterate_latches():
temp = BDD.make_eq(BDD(self.get_primed_var(x.lit)),
self.lit2bdd(x.next))
b &= temp.and_abstract(
strat,
BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.iterate_controllable_inputs())))
b = b.restrict(src_states_bdd)
b &= src_states_bdd
b = b.exist_abstract(
BDD.make_cube(
imap(
funcomp(BDD, symbol_lit),
chain(self.iterate_latches(),
self.iterate_uncontrollable_inputs()))))
return self.unprime_latches_in_bdd(b)
def upost(self, q):
assert isinstance(q, BDD)
if q in self.succ_cache:
return iter(self.succ_cache[q])
A = BDD.true()
M = set()
while A != BDD.false():
a = A.get_one_minterm(self.uinputs)
trans = BDD.make_cube(
imap(
lambda x: BDD.make_eq(
BDD(self.aig.get_primed_var(x.lit)),
self.aig.lit2bdd(x.next).and_abstract(
q, self.latch_cube)), self.aig.iterate_latches()))
lhs = trans & a
rhs = self.aig.prime_all_inputs_in_bdd(trans)
simd = BDD.make_impl(lhs, rhs).univ_abstract(self.platch_cube)\
.exist_abstract(self.pcinputs_cube)\
.univ_abstract(self.cinputs_cube)
simd = self.aig.unprime_all_inputs_in_bdd(simd)
A &= ~simd
Mp = set()
for m in M:
if not (BDD.make_impl(m, simd) == BDD.true()):
Mp.add(m)
M = Mp
M.add(a)
log.DBG_MSG("Upost |M| = " + str(len(M)))
self.succ_cache[q] = map(lambda x: (q, x), M)
return iter(self.succ_cache[q])
def extract_output_funs(self, strategy, care_set=None):
"""
Calculate BDDs for output functions given non-deterministic winning
strategy.
"""
if care_set is None:
care_set = BDD.true()
output_models = dict()
all_outputs = [BDD(x.lit) for x in self.iterate_controllable_inputs()]
for c_symb in self.iterate_controllable_inputs():
c = BDD(c_symb.lit)
others = set(set(all_outputs) - set([c]))
if others:
others_cube = BDD.make_cube(others)
c_arena = strategy.exist_abstract(others_cube)
else:
c_arena = strategy
# pairs (x,u) in which c can be true
can_be_true = c_arena.cofactor(c)
# pairs (x,u) in which c can be false
can_be_false = c_arena.cofactor(~c)
must_be_true = (~can_be_false) & can_be_true
must_be_false = (~can_be_true) & can_be_false
local_care_set = care_set & (must_be_true | must_be_false)
# Restrict operation:
# on care_set: must_be_true.restrict(care_set) <-> must_be_true
c_model = min([must_be_true.safe_restrict(local_care_set),
(~must_be_false).safe_restrict(local_care_set)],
key=lambda x: x.dag_size())
output_models[c_symb.lit] = c_model
log.DBG_MSG("Size of function for " + str(c.get_index()) + " = " +
str(c_model.dag_size()))
strategy &= BDD.make_eq(c, c_model)
return output_models
def upost(self, q):
assert isinstance(q, BDD)
if q in self.succ_cache:
return iter(self.succ_cache[q])
A = BDD.true()
M = set()
while A != BDD.false():
a = A.get_one_minterm(self.uinputs)
trans = BDD.make_cube(
imap(lambda x: BDD.make_eq(BDD(self.aig.get_primed_var(x.lit)),
self.aig.lit2bdd(x.next)
.and_abstract(q, self.latch_cube)),
self.aig.iterate_latches()))
lhs = trans & a
rhs = self.aig.prime_all_inputs_in_bdd(trans)
simd = BDD.make_impl(lhs, rhs).univ_abstract(self.platch_cube)\
.exist_abstract(self.pcinputs_cube)\
.univ_abstract(self.cinputs_cube)
simd = self.aig.unprime_all_inputs_in_bdd(simd)
A &= ~simd
Mp = set()
for m in M:
if not (BDD.make_impl(m, simd) == BDD.true()):
Mp.add(m)
M = Mp
M.add(a)
log.DBG_MSG("Upost |M| = " + str(len(M)))
self.succ_cache[q] = map(lambda x: (q, x), M)
return iter(self.succ_cache[q])
def post_bdd(self,
src_states_bdd,
sys_strat=None,
use_trans=False,
over_approx=False):
"""
POST = EL.EXu.EXc : src(L) ^ T(L,Xu,Xc,L') [^St(L,Xu,Xc)]
optional argument fixes possible actions for the environment
"""
if not use_trans or over_approx:
return self.over_post_bdd(src_states_bdd, sys_strat)
transition_bdd = self.trans_rel_bdd()
trans = transition_bdd
if sys_strat is not None:
trans &= sys_strat
trans = trans.restrict(src_states_bdd)
suc_bdd = trans.and_abstract(
src_states_bdd,
BDD.make_cube(
imap(
funcomp(BDD, symbol_lit),
chain(self.iterate_controllable_inputs(),
self.iterate_uncontrollable_inputs(),
self.iterate_latches()))))
return self.unprime_latches_in_bdd(suc_bdd)
def cpre_bdd(self, dst_states_bdd, get_strat=False, use_trans=False):
""" CPRE = AXu.EXc.EL' : T(L,Xu,Xc,L') ^ dst(L') """
# take a transition step backwards
p_bdd = self.substitute_latches_next(dst_states_bdd,
use_trans=use_trans)
# for all uncontrollable action there is a contro...
# note: if argument get_strat == True then we leave the "good"
# controllable actions in the bdd
if not get_strat:
p_bdd = p_bdd.exist_abstract(
BDD.make_cube(imap(funcomp(BDD, symbol_lit),
self.iterate_controllable_inputs())))
p_bdd = p_bdd.univ_abstract(
BDD.make_cube(imap(funcomp(BDD, symbol_lit),
self.iterate_uncontrollable_inputs())))
return p_bdd
def strat_is_inductive(self, strat, use_trans=False):
strat_dom = strat.exist_abstract(
BDD.make_cube(imap(funcomp(BDD, symbol_lit),
chain(self.iterate_controllable_inputs(),
self.iterate_uncontrollable_inputs()))))
p_bdd = self.substitute_latches_next(strat_dom, use_trans=use_trans)
return BDD.make_impl(strat, p_bdd) == BDD.true()
def cpre_bdd(self, dst_states_bdd, get_strat=False, use_trans=False):
""" CPRE = AXu.EXc.EL' : T(L,Xu,Xc,L') ^ dst(L') """
# take a transition step backwards
p_bdd = self.substitute_latches_next(dst_states_bdd,
use_trans=use_trans)
# for all uncontrollable action there is a contro...
# note: if argument get_strat == True then we leave the "good"
# controllable actions in the bdd
if not get_strat:
p_bdd = p_bdd.exist_abstract(
BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.iterate_controllable_inputs())))
p_bdd = p_bdd.univ_abstract(
BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.iterate_uncontrollable_inputs())))
return p_bdd
def strat_is_inductive(self, strat, use_trans=False):
strat_dom = strat.exist_abstract(
BDD.make_cube(
imap(
funcomp(BDD, symbol_lit),
chain(self.iterate_controllable_inputs(),
self.iterate_uncontrollable_inputs()))))
p_bdd = self.substitute_latches_next(strat_dom, use_trans=use_trans)
return BDD.make_impl(strat, p_bdd) == BDD.true()
def __init__(self, aig):
self.aig = aig
self.uinputs = [
x.lit for x in self.aig.iterate_uncontrollable_inputs()
]
self.latches = [x.lit for x in self.aig.iterate_latches()]
self.latch_cube = BDD.make_cube(
imap(funcomp(BDD, symbol_lit), self.aig.iterate_latches()))
self.platch_cube = BDD.make_cube(
imap(funcomp(BDD, self.aig.get_primed_var, symbol_lit),
self.aig.iterate_latches()))
self.cinputs_cube = BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.aig.iterate_controllable_inputs()))
self.pcinputs_cube = self.aig.prime_all_inputs_in_bdd(
self.cinputs_cube)
self.uinputs_cube = BDD.make_cube(
imap(funcomp(BDD, symbol_lit),
self.aig.iterate_uncontrollable_inputs()))
self.init_state_bdd = self.aig.init_state_bdd()
self.error_bdd = self.aig.lit2bdd(self.aig.error_fake_latch.lit)
self.Venv = dict()
self.Venv[self.init_state_bdd] = True
self.succ_cache = dict()
def over_post_bdd(self, src_states_bdd, sys_strat=None):
""" Over-approximated version of concrete post which can be done even
without the transition relation """
strat = BDD.true()
if sys_strat is not None:
strat &= sys_strat
# to do this, we use an over-simplified transition relation, EXu,Xc
b = BDD.true()
for x in self.iterate_latches():
temp = BDD.make_eq(BDD(self.get_primed_var(x.lit)),
self.lit2bdd(x.next))
b &= temp.and_abstract(
strat,
BDD.make_cube(imap(
funcomp(BDD, symbol_lit),
self.iterate_controllable_inputs()
)))
b = b.restrict(src_states_bdd)
b &= src_states_bdd
b = b.exist_abstract(
BDD.make_cube(imap(funcomp(BDD, symbol_lit),
chain(self.iterate_latches(),
self.iterate_uncontrollable_inputs()))))
return self.unprime_latches_in_bdd(b)
def substitute_latches_next(self, b, use_trans=False, restrict_fun=None):
if use_trans:
transition_bdd = self.trans_rel_bdd()
trans = transition_bdd
if restrict_fun is not None:
trans = trans.restrict(restrict_fun)
primed_bdd = self.prime_latches_in_bdd(b)
primed_latches = BDD.make_cube(
imap(funcomp(BDD, self.get_primed_var, symbol_lit),
self.iterate_latches()))
return trans.and_abstract(primed_bdd, primed_latches)
else:
latches = [x.lit for x in self.iterate_latches()]
latch_funs = [self.lit2bdd(x.next) for x in self.iterate_latches()]
if restrict_fun is not None:
latch_funs = [x.restrict(restrict_fun) for x in latch_funs]
# take a transition step backwards
return b.compose(latches, latch_funs)
def substitute_latches_next(self, b, use_trans=False, restrict_fun=None):
if use_trans:
transition_bdd = self.trans_rel_bdd()
trans = transition_bdd
if restrict_fun is not None:
trans = trans.restrict(restrict_fun)
primed_bdd = self.prime_latches_in_bdd(b)
primed_latches = BDD.make_cube(
imap(funcomp(BDD, self.get_primed_var, symbol_lit),
self.iterate_latches()))
return trans.and_abstract(primed_bdd,
primed_latches)
else:
latches = [x.lit for x in self.iterate_latches()]
latch_funs = [self.lit2bdd(x.next) for x in
self.iterate_latches()]
if restrict_fun is not None:
latch_funs = [x.restrict(restrict_fun) for x in latch_funs]
# take a transition step backwards
return b.compose(latches, latch_funs)
def decompose(aig, argv):
if argv.decomp == 1:
if lit_is_negated(aig.error_fake_latch.next):
log.DBG_MSG("Decomposition opt possible (BIG OR case)")
(A, B) = aig.get_1l_land(strip_lit(aig.error_fake_latch.next))
return imap(
lambda a: ConcGame(BDDAIG(aig).short_error(a),
use_trans=argv.use_trans),
merge_some_signals(BDD.true(), A, aig, argv))
else:
(A, B) = aig.get_1l_land(aig.error_fake_latch.next)
if not B:
log.DBG_MSG("No decomposition opt possible")
return None
else:
log.DBG_MSG("Decomposition opt possible (A ^ [C v D] case)")
log.DBG_MSG(str(len(A)) + " AND leaves: " + str(A))
# critical heuristic: which OR leaf do we distribute?
# here I propose to choose the one with the most children
b = B.pop()
(C, D) = aig.get_1l_land(b)
for bp in B:
(Cp, Dp) = aig.get_1l_land(bp)
if len(Cp) > len(C):
b = bp
C = Cp
log.DBG_MSG("Chosen OR: " + str(b))
rem_AND_leaves = filter(lambda x: strip_lit(x) != b, A)
rdeps = set()
for r in rem_AND_leaves:
rdeps |= aig.get_lit_deps(strip_lit(r))
log.DBG_MSG("Rem. AND leaves' deps: " + str(rdeps))
cube = BDD.make_cube(map(aig.lit2bdd, rem_AND_leaves))
log.DBG_MSG(
str(len(C)) + " OR leaves: " + str(map(aig.get_lit_name, C)))
return imap(
lambda a: ConcGame(BDDAIG(aig).short_error(a),
use_trans=argv.use_trans),
merge_some_signals(cube, C, aig, argv))
elif argv.decomp == 2:
raise NotImplementedError
def decompose(aig, argv):
if argv.decomp == 1:
if lit_is_negated(aig.error_fake_latch.next):
log.DBG_MSG("Decomposition opt possible (BIG OR case)")
(A, B) = aig.get_1l_land(strip_lit(aig.error_fake_latch.next))
return imap(lambda a: ConcGame(
BDDAIG(aig).short_error(a),
use_trans=argv.use_trans),
merge_some_signals(BDD.true(), A, aig, argv))
else:
(A, B) = aig.get_1l_land(aig.error_fake_latch.next)
if not B:
log.DBG_MSG("No decomposition opt possible")
return None
else:
log.DBG_MSG("Decomposition opt possible (A ^ [C v D] case)")
log.DBG_MSG(str(len(A)) + " AND leaves: " + str(A))
# critical heuristic: which OR leaf do we distribute?
# here I propose to choose the one with the most children
b = B.pop()
(C, D) = aig.get_1l_land(b)
for bp in B:
(Cp, Dp) = aig.get_1l_land(bp)
if len(Cp) > len(C):
b = bp
C = Cp
log.DBG_MSG("Chosen OR: " + str(b))
rem_AND_leaves = filter(lambda x: strip_lit(x) != b, A)
rdeps = set()
for r in rem_AND_leaves:
rdeps |= aig.get_lit_deps(strip_lit(r))
log.DBG_MSG("Rem. AND leaves' deps: " + str(rdeps))
cube = BDD.make_cube(map(aig.lit2bdd, rem_AND_leaves))
log.DBG_MSG(str(len(C)) + " OR leaves: " +
str(map(aig.get_lit_name, C)))
return imap(lambda a: ConcGame(
BDDAIG(aig).short_error(a),
use_trans=argv.use_trans), merge_some_signals(cube, C, aig,
argv))
elif argv.decomp == 2:
raise NotImplementedError
def post_bdd(self, src_states_bdd, sys_strat=None,
use_trans=False, over_approx=False):
"""
POST = EL.EXu.EXc : src(L) ^ T(L,Xu,Xc,L') [^St(L,Xu,Xc)]
optional argument fixes possible actions for the environment
"""
if not use_trans or over_approx:
return self.over_post_bdd(src_states_bdd, sys_strat)
transition_bdd = self.trans_rel_bdd()
trans = transition_bdd
if sys_strat is not None:
trans &= sys_strat
trans = trans.restrict(src_states_bdd)
suc_bdd = trans.and_abstract(
src_states_bdd,
BDD.make_cube(imap(funcomp(BDD, symbol_lit), chain(
self.iterate_controllable_inputs(),
self.iterate_uncontrollable_inputs(),
self.iterate_latches())
)))
return self.unprime_latches_in_bdd(suc_bdd)
def extract_output_funs(self, strategy, care_set=None):
"""
Calculate BDDs for output functions given non-deterministic winning
strategy.
"""
if care_set is None:
care_set = BDD.true()
output_models = dict()
all_outputs = [BDD(x.lit) for x in self.iterate_controllable_inputs()]
for c_symb in self.iterate_controllable_inputs():
c = BDD(c_symb.lit)
others = set(set(all_outputs) - set([c]))
if others:
others_cube = BDD.make_cube(others)
c_arena = strategy.exist_abstract(others_cube)
else:
c_arena = strategy
# pairs (x,u) in which c can be true
can_be_true = c_arena.cofactor(c)
# pairs (x,u) in which c can be false
can_be_false = c_arena.cofactor(~c)
must_be_true = (~can_be_false) & can_be_true
must_be_false = (~can_be_true) & can_be_false
local_care_set = care_set & (must_be_true | must_be_false)
# Restrict operation:
# on care_set: must_be_true.restrict(care_set) <-> must_be_true
c_model = min([
must_be_true.safe_restrict(local_care_set),
(~must_be_false).safe_restrict(local_care_set)
],
key=lambda x: x.dag_size())
output_models[c_symb.lit] = c_model
log.DBG_MSG("Size of function for " + str(c.get_index()) + " = " +
str(c_model.dag_size()))
strategy &= BDD.make_eq(c, c_model)
return output_models
def cpost(self, s):
assert isinstance(s, tuple)
q = s[0]
au = s[1]
if s in self.succ_cache:
L = self.succ_cache[s]
else:
L = BDD.make_cube(
imap(lambda x: BDD.make_eq(BDD(x.lit),
self.aig.lit2bdd(x.next)
.and_abstract(q & au,
self.latch_cube &
self.uinputs_cube)),
self.aig.iterate_latches()))\
.exist_abstract(self.cinputs_cube)
self.succ_cache[s] = L
M = set()
while L != BDD.false():
l = L.get_one_minterm(self.latches)
L &= ~l
self.Venv[l] = True
M.add(l)
log.DBG_MSG("Cpost |M| = " + str(len(M)))
return iter(M)
def cpost(self, s):
assert isinstance(s, tuple)
q = s[0]
au = s[1]
if s in self.succ_cache:
L = self.succ_cache[s]
else:
L = BDD.make_cube(
imap(lambda x: BDD.make_eq(BDD(x.lit),
self.aig.lit2bdd(x.next)
.and_abstract(q & au,
self.latch_cube &
self.uinputs_cube)),
self.aig.iterate_latches()))\
.exist_abstract(self.cinputs_cube)
self.succ_cache[s] = L
M = set()
while L != BDD.false():
l = L.get_one_minterm(self.latches)
L &= ~l
self.Venv[l] = True
M.add(l)
log.DBG_MSG("Cpost |M| = " + str(len(M)))
return iter(M)
def comp_synth4(games, gen_game):
s = None
cum_s = None
cum_w = None
cnt = 0
triple_list = []
for game in games:
assert isinstance(game, BackwardGame)
w = backward_safety_synth(game)
cnt += 1
# short-circuit a negative response
if w is None:
log.DBG_MSG("Short-circuit exit 1 after sub-game #" + str(cnt))
return None
s = game.cpre(w, get_strat=True)
if cum_s is None:
cum_s = s
cum_w = w
else:
cum_s &= s
cum_w &= w
# another short-circuit exit
if (not cum_s or not game.init() & cum_s):
log.DBG_MSG("Short-circuit exit 2 after sub-game #" + str(cnt))
return None
triple_list.append((game, s, w))
log.DBG_MSG("Solved " + str(cnt) + " sub games.")
# lets simplify transition functions
gen_game.aig.restrict_latch_next_funs(cum_s)
# what comes next is a fixpoint computation using a UPRE
# step at a time in the global game and using it to get more
# information from the local sub-games
lose = BDD.true()
lose_next = ~cum_w | gen_game.error()
while lose_next != lose:
lose = lose_next
log.DBG_MSG("Doing global UPRE")
lose_next = lose | gen_game.upre(lose)
for i in range(len(triple_list)):
wt = triple_list[i][2]
gamet = triple_list[i][0]
local_deps = set([x.lit for x in gamet.aig.iterate_latches()])
rem_lats = gen_game.aig.get_bdd_latch_deps(lose_next) - local_deps
pt = lose_next
if rem_lats:
pt = lose_next.univ_abstract(BDD.make_cube(map(BDD, rem_lats)))
# log.BDD_DMP(lose_next, "global losing area iterate")
# log.BDD_DMP(pt, "new losing area")
assert BDD.make_impl(~wt, pt) == BDD.true()
if BDD.make_impl(pt, ~wt) != BDD.true():
gamet.short_error = pt
wt = backward_safety_synth(gamet)
if (wt is None or not gamet.init() & wt):
log.DBG_MSG("Short-circuit exit 3")
return None
st = gamet.cpre(wt, get_strat=True)
gen_game.aig.restrict_latch_next_funs(wt)
triple_list[i] = (gamet, st, wt)
for t in triple_list:
lose_next |= ~t[2]
# after the fixpoint has been reached we can compute the error
win = ~lose
if (not win or not gen_game.init() & win):
return None
else:
return win
def comp_synth4(games, gen_game):
s = None
cum_s = None
cum_w = None
cnt = 0
triple_list = []
for game in games:
assert isinstance(game, BackwardGame)
w = backward_safety_synth(game)
cnt += 1
# short-circuit a negative response
if w is None:
log.DBG_MSG("Short-circuit exit 1 after sub-game #" + str(cnt))
return None
s = game.cpre(w, get_strat=True)
if cum_s is None:
cum_s = s
cum_w = w
else:
cum_s &= s
cum_w &= w
# another short-circuit exit
if (not cum_s or not game.init() & cum_s):
log.DBG_MSG("Short-circuit exit 2 after sub-game #" + str(cnt))
return None
triple_list.append((game, s, w))
log.DBG_MSG("Solved " + str(cnt) + " sub games.")
# lets simplify transition functions
gen_game.aig.restrict_latch_next_funs(cum_s)
# what comes next is a fixpoint computation using a UPRE
# step at a time in the global game and using it to get more
# information from the local sub-games
lose = BDD.true()
lose_next = ~cum_w | gen_game.error()
while lose_next != lose:
lose = lose_next
log.DBG_MSG("Doing global UPRE")
lose_next = lose | gen_game.upre(lose)
for i in range(len(triple_list)):
wt = triple_list[i][2]
gamet = triple_list[i][0]
local_deps = set([x.lit for x in gamet.aig.iterate_latches()])
rem_lats = gen_game.aig.get_bdd_latch_deps(lose_next) - local_deps
pt = lose_next
if rem_lats:
pt = lose_next.univ_abstract(
BDD.make_cube(map(BDD, rem_lats)))
# log.BDD_DMP(lose_next, "global losing area iterate")
# log.BDD_DMP(pt, "new losing area")
assert BDD.make_impl(~wt, pt) == BDD.true()
if BDD.make_impl(pt, ~wt) != BDD.true():
gamet.short_error = pt
wt = backward_safety_synth(gamet)
if (wt is None or not gamet.init() & wt):
log.DBG_MSG("Short-circuit exit 3")
return None
st = gamet.cpre(wt, get_strat=True)
gen_game.aig.restrict_latch_next_funs(wt)
triple_list[i] = (gamet, st, wt)
for t in triple_list:
lose_next |= ~t[2]
# after the fixpoint has been reached we can compute the error
win = ~lose
if (not win or not gen_game.init() & win):
return None
else:
return win
