def minimize_counterexample_normal(hypothesis, system, ctx):
reset = []
current_state = hypothesis.init_state
current_clock = 0
LTWs = []
for tw in ctx:
current_clock = current_clock + tw.time
LTWs.append(TimedWord(tw.action, current_clock))
for tran in hypothesis.trans:
if current_state == tran.source and tran.is_passing_tran(TimedWord(tw.action, current_clock)):
reset.append(tran.reset)
current_state = tran.target
if tran.reset:
current_clock = 0
break
for i in range(len(LTWs)):
while True:
if i == 0 or reset[i - 1]:
can_reduce = (LTWs[i].time > 0)
else:
can_reduce = (LTWs[i].time > LTWs[i - 1].time)
if not can_reduce:
break
LTWs_temp = copy.deepcopy(LTWs)
LTWs_temp[i] = TimedWord(LTWs[i].action, one_lower(LTWs[i].time))
flag, ctx = is_counterexample_normal(hypothesis, system, LTW_to_DTW(LTWs_temp, reset))
if not flag:
break
LTWs = LTWs_temp
return LTW_to_DTW(LTWs, reset)
def is_consistent(self):
flag = True
consistent_add = []
table_element = [s for s in self.S] + [r for r in self.R]
for i in range(0, len(table_element) - 1):
for j in range(i + 1, len(table_element)):
if table_element[i].values == table_element[j].values and table_element[i].suffixes_resets == table_element[j].suffixes_resets:
temp_elements1 = []
temp_elements2 = []
for element in table_element:
if is_prefix(element.LRTWs, table_element[i].LRTWs):
temp_elements1.append(element)
if is_prefix(element.LRTWs, table_element[j].LRTWs):
temp_elements2.append(element)
for e1 in temp_elements1:
for e2 in temp_elements2:
newLRTWs1 = delete_prefix(e1.LRTWs, table_element[i].LRTWs)
newLRTWs2 = delete_prefix(e2.LRTWs, table_element[j].LRTWs)
if len(newLRTWs1) == len(newLRTWs2) == 1:
if newLRTWs1[0].action == newLRTWs2[0].action and newLRTWs1[0].time == newLRTWs2[0].time:
if newLRTWs1[0].reset != newLRTWs2[0].reset:
flag = False
consistent_add = [TimedWord(newLRTWs1[0].action, newLRTWs1[0].time)]
return flag, consistent_add
if e1.values != e2.values or e1.suffixes_resets != e2.suffixes_resets:
flag = False
for k in range(0, len(e1.values)):
if e1.values[k] != e2.values[k] or e1.suffixes_resets[k] != e2.suffixes_resets[k]:
new_index = k
consistent_add = [TimedWord(newLRTWs1[0].action, newLRTWs1[0].time)] + self.E[new_index]
return flag, consistent_add
return flag, consistent_add
def LTW_to_DTW(LTWs, reset):
DTWs = []
for j in range(len(LTWs)):
if j == 0 or reset[j - 1]:
DTWs.append(TimedWord(LTWs[j].action, LTWs[j].time))
else:
DTWs.append(TimedWord(LTWs[j].action, LTWs[j].time - LTWs[j - 1].time))
return DTWs
def test_DTWs_normal(self, DTWs):
outputs = []
now_time = 0
cur_state = self.init_state
for dtw in DTWs:
if cur_state == self.sink_state:
outputs.append(-1)
else:
time = dtw.time + now_time
new_LTW = TimedWord(dtw.action, time)
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(
new_LTW):
cur_state = tran.target
if tran.reset:
now_time = 0
else:
now_time = time
break
if cur_state in self.accept_states:
outputs.append(1)
elif cur_state == self.sink_state:
outputs.append(-1)
else:
outputs.append(0)
return outputs
def minimize_counterexample(hypothesis, system, ctx):
# Find sequence of reset information
reset = []
DRTWs, outputs = system.test_DTWs(ctx)
for drtw in DRTWs:
reset.append(drtw.reset)
# ctx to LTWs
LTWs = LRTW_to_LTW(DRTW_to_LRTW(DRTWs))
# start minimize
for i in range(len(LTWs)):
while True:
if i == 0 or reset[i - 1]:
can_reduce = (LTWs[i].time > 0)
else:
can_reduce = (LTWs[i].time > LTWs[i - 1].time)
if not can_reduce:
break
LTWs_temp = copy.deepcopy(LTWs)
LTWs_temp[i] = TimedWord(LTWs[i].action, one_lower(LTWs[i].time))
flag, ctx = is_counterexample(hypothesis, system,
LTW_to_DTW(LTWs_temp, reset))
if not flag:
break
LTWs = copy.deepcopy(LTWs_temp)
return LTW_to_DTW(LTWs, reset)
def find_DTWs(letterword):
path = find_path(letterword)
DTWs = []
current_clock_valuation = 0
delay_time = 0
for letterword in path:
if len(letterword.lw) == 1:
letter1, letter2 = list(letterword.lw[0])
elif len(letterword.lw) == 2:
letter1, letter2 = list(letterword.lw[0])[0], list(
letterword.lw[1])[0]
else:
raise NotImplementedError()
if letter1.flag == 'A': # "A" or "B"?
temp_region = letter1.guard
else:
temp_region = letter2.guard
if letterword.action == "DELAY":
delay_time = minimum_in_region(
temp_region) - current_clock_valuation
current_clock_valuation = minimum_in_region(temp_region)
elif letterword.action == 'INIT':
pass
else:
new_timedword = TimedWord(letterword.action, delay_time)
DTWs.append(new_timedword)
current_clock_valuation = minimum_in_region(temp_region)
return DTWs
def test_DTW_normal(self, DTW, now_time, cur_state):
value = None
reset = False
tran_flag = False # tranFlag为true表示有这样的迁移
if DTW is None:
if cur_state in self.accept_states:
value = 1
else:
value = 0
else:
LTW = TimedWord(DTW.action, DTW.time + now_time)
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(LTW):
tran_flag = True
cur_state = tran.target
if tran.reset:
reset = True
break
if not tran_flag:
value = -1
cur_state = 'sink'
reset = True
if cur_state in self.accept_states:
value = 1
elif cur_state != 'sink':
value = 0
return cur_state, value, reset
def test_DTWs(self, DTWs):
DRTWs = []
now_time = 0
cur_state = self.init_state
for dtw in DTWs:
if cur_state == self.sink_state:
DRTWs.append(ResetTimedWord(dtw.action, dtw.time, True))
else:
time = dtw.time + now_time
new_LTW = TimedWord(dtw.action, time)
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(
new_LTW):
cur_state = tran.target
if tran.reset:
now_time = 0
reset = True
else:
now_time = time
reset = False
DRTWs.append(
ResetTimedWord(dtw.action, dtw.time, reset))
break
if cur_state in self.accept_states:
value = 1
elif cur_state == self.sink_state:
value = -1
else:
value = 0
return DRTWs, value
def test_DTWs_normal(self, DTWs, is_mq=False):
if is_mq:
self.mq_num += 1
else:
self.test_num += 1
value = 0
now_time = 0
cur_state = self.init_state
for dtw in DTWs:
time = dtw.time + now_time
new_LTW = TimedWord(dtw.action, time)
flag = False
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(new_LTW):
flag = True
cur_state = tran.target
if tran.reset:
now_time = 0
else:
now_time = time
break
if not flag:
value = -1
break
if value != -1:
if cur_state in self.accept_states:
value = 1
else:
value = 0
return value
def init_table_normal(actions, system):
if system.init_state in system.accept_states:
init_value = 1
else:
init_value = 0
S = [Element([], [init_value], [[]])]
R = []
E = [[]]
tables = [ObsTable(S, R, E, parent=-1, reason="init")]
for i in range(0, len(actions)):
temp_tables = []
for table in tables:
new_DTWs = [TimedWord(actions[i], 0)] # 同样也是LTWs
outputs = system.test_DTWs_normal(new_DTWs, True)
if outputs[-1] == -1: # now at sink
guesses = [True]
else:
guesses = [True, False]
for guess in guesses:
new_LRTWs = [
ResetTimedWord(new_DTWs[0].action, new_DTWs[0].time, guess)
]
new_element = Element(new_LRTWs, [outputs[-1]], [[]])
temp_R = table.R + [new_element]
new_table = ObsTable(deepcopy(S),
deepcopy(temp_R),
deepcopy(E),
parent=-1,
reason="init")
temp_tables.append(new_table)
tables = temp_tables
return tables
def sample_generation_main_old_1(actions, upperGuard, stateNum):
sample = []
length = random.randint(1, stateNum * 2)
for i in range(length):
action = actions[random.randint(0, len(actions) - 1)]
time = random.randint(0, upperGuard * 2 + 1)
if time % 2 == 0:
time = time // 2
else:
time = time // 2 + 0.5
temp = TimedWord(action, time)
sample.append(temp)
return sample
def extend_R(s, actions, table, system):
table_LRTWS = [s.LRTWs for s in table.S] + [r.LRTWs for r in table.R]
for action in actions:
LTWs = LRTW_to_LTW(s.LRTWs) + [TimedWord(action, 0)]
LRTWs, value = TQs(LTWs, system)
system.mq_num -= 1
if value == -1:
element = fill_table_row(LRTWs, table, True, system)
else:
element = fill_table_row(LRTWs, table, False, system)
if element.LRTWs not in table_LRTWS:
table.R.append(element)
return table
def sample_generation_custom(upper_guard, length, system):
# 注意，通用采样情况下测试集可能是无效的，也就是可能会到达sink状态
sample = None
while sample is None:
sample = sample_generation_valid(upper_guard, length, system)
action = random.choice(system.actions)
time = random.randint(0, upper_guard * 3 + 1)
if time % 2 == 0:
time = time // 2
else:
time = time // 2 + 0.5
index = random.randint(0, len(sample) - 1)
sample[index] = TimedWord(action, time) # 随机替换其中一个
return sample
def test_DTWs(self, DTWs):
self.test_num += 1
tuple_DTWs = tuple(DTWs)
if tuple_DTWs in self.cache:
return self.cache[tuple_DTWs][0], self.cache[tuple_DTWs][1]
self.test_num_cache += 1
DRTWs = []
outputs = []
now_time = 0
cur_state = self.init_state
for dtw in DTWs:
self.action_num += 1
time = dtw.time + now_time
new_LTW = TimedWord(dtw.action, time)
flag = False
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(new_LTW):
flag = True
cur_state = tran.target
if tran.reset:
now_time = 0
reset = True
else:
now_time = time
reset = False
DRTWs.append(ResetTimedWord(dtw.action, dtw.time, reset))
if cur_state in self.accept_states:
outputs.append(1)
else:
outputs.append(0)
break
if not flag:
DRTWs.append(ResetTimedWord(dtw.action, dtw.time, True))
outputs.append(-1)
break
# 补全
len_diff = len(DTWs) - len(DRTWs)
if len_diff != 0:
temp = DTWs[len(DRTWs):]
for i in temp:
DRTWs.append(ResetTimedWord(i.action, i.time, True))
outputs.append(-1)
self.cache[tuple_DTWs] = [DRTWs, outputs]
return DRTWs, outputs
def test_DTWs_normal(self, DTWs):
now_time = 0
cur_state = self.init_state
for dtw in DTWs:
time = dtw.time + now_time
new_LTW = TimedWord(dtw.action, time)
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(new_LTW):
cur_state = tran.target
if tran.reset:
now_time = 0
else:
now_time = time
if cur_state == self.sink_state:
return -1
break
if cur_state in self.accept_states:
value = 1
else:
value = 0
return value
def test_LTWs(self, LTWs):
self.mq_num += 1
if not LTWs:
if self.init_state in self.accept_states:
value = 1
else:
value = 0
return [], value
else:
LRTWs = []
value = None
now_time = 0
cur_state = self.init_state
for ltw in LTWs:
if ltw.time < now_time:
value = -1
LRTWs.append(ResetTimedWord(ltw.action, ltw.time, True))
break
else:
DTW = TimedWord(ltw.action, ltw.time - now_time)
cur_state, value, reset = self.test_DTW(
DTW, now_time, cur_state)
if reset:
LRTWs.append(ResetTimedWord(ltw.action, ltw.time,
True))
now_time = 0
else:
LRTWs.append(
ResetTimedWord(ltw.action, ltw.time, False))
now_time = ltw.time
if value == -1:
break
# 补全
len_diff = len(LTWs) - len(LRTWs)
if len_diff != 0:
temp = LTWs[len(LRTWs):]
for i in temp:
LRTWs.append(ResetTimedWord(i.action, i.time, True))
return LRTWs, value
def test_DTWs_normal(self, DTWs, is_mq=False):
tuple_DTWs = tuple(DTWs)
if is_mq:
self.mq_num += 1
else:
self.test_num += 1
if tuple_DTWs in self.cache:
return self.cache[tuple_DTWs][0]
self.test_num_cache += 1
outputs = []
now_time = 0
cur_state = self.init_state
for dtw in DTWs:
self.action_num += 1
time = dtw.time + now_time
new_LTW = TimedWord(dtw.action, time)
flag = False
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(new_LTW):
flag = True
cur_state = tran.target
if tran.reset:
now_time = 0
else:
now_time = time
break
if not flag:
outputs.append(-1)
break
if cur_state in self.accept_states:
outputs.append(1)
else:
outputs.append(0)
# 补全
len_diff = len(DTWs) - len(outputs)
if len_diff != 0:
outputs.extend([-1] * len_diff)
self.cache[tuple_DTWs] = [outputs]
return outputs
def test_DTWs(self, DTWs):
self.test_num += 1
DRTWs = []
value = None
now_time = 0
cur_state = self.init_state
for dtw in DTWs:
time = dtw.time + now_time
new_LTW = TimedWord(dtw.action, time)
flag = False
for tran in self.trans:
if tran.source == cur_state and tran.is_passing_tran(new_LTW):
flag = True
cur_state = tran.target
if tran.reset:
now_time = 0
reset = True
else:
now_time = time
reset = False
DRTWs.append(ResetTimedWord(dtw.action, dtw.time, reset))
break
if not flag:
DRTWs.append(ResetTimedWord(dtw.action, dtw.time, True))
value = -1
break
# 补全
len_diff = len(DTWs) - len(DRTWs)
if len_diff != 0:
temp = DTWs[len(DRTWs):]
for i in temp:
DRTWs.append(ResetTimedWord(i.action, i.time, True))
if value != -1:
if cur_state in self.accept_states:
value = 1
else:
value = 0
return DRTWs, value
def is_consistent(self):
flag = True
e_index = 0
prefix_LTWs = []
reset_i = []
reset_j = []
index_i = 0
index_j = 0
table_element = [s for s in self.S] + [r for r in self.R]
for i in range(0, len(table_element) - 1):
for j in range(i + 1, len(table_element)):
if table_element[i].values == table_element[
j].values and table_element[
i].suffixes_resets == table_element[
j].suffixes_resets:
temp_elements1 = []
temp_elements2 = []
for element in table_element:
if is_prefix(element.LRTWs, table_element[i].LRTWs):
temp_elements1.append(element)
if is_prefix(element.LRTWs, table_element[j].LRTWs):
temp_elements2.append(element)
for e1 in temp_elements1:
for e2 in temp_elements2:
newLRTWs1 = delete_prefix(e1.LRTWs,
table_element[i].LRTWs)
newLRTWs2 = delete_prefix(e2.LRTWs,
table_element[j].LRTWs)
if len(newLRTWs1) == len(newLRTWs2) == 1:
if newLRTWs1[0].action == newLRTWs2[
0].action and newLRTWs1[
0].time == newLRTWs2[0].time:
if newLRTWs1[0].reset != newLRTWs2[0].reset:
flag = False
e_index = 0
prefix_LTWs = [
TimedWord(newLRTWs1[0].action,
newLRTWs1[0].time)
]
reset_i = [newLRTWs1[0].reset]
reset_j = [newLRTWs2[0].reset]
index_i = i
index_j = j
return flag, prefix_LTWs, e_index, reset_i, reset_j, index_i, index_j
if e1.values != e2.values or e1.suffixes_resets != e2.suffixes_resets:
flag = False
prefix_LTWs = [
TimedWord(newLRTWs1[0].action,
newLRTWs1[0].time)
]
for k in range(0, len(e1.values)):
if e1.values[k] != e2.values[
k] or e1.suffixes_resets != e2.suffixes_resets:
e_index = k
reset_i = [
newLRTWs1[0].reset
] + table_element[
i].suffixes_resets[k]
reset_j = [
newLRTWs2[0].reset
] + table_element[
j].suffixes_resets[k]
index_i = i
index_j = j
return flag, prefix_LTWs, e_index, reset_i, reset_j, index_i, index_j
return flag, prefix_LTWs, e_index, reset_i, reset_j, index_i, index_j
def sample_generation_valid(upper_guard, length, system):
# First produce a path (as a list of transitions) in the OTA
path = []
cur_state = system.init_state
for i in range(length):
edges = []
for tran in system.trans:
if cur_state == tran.source:
edges.append(tran)
edge = random.choice(edges)
path.append(edge)
cur_state = edge.target
# Next, figure out (double of) the minimum and maximum logical time of each edge in path.
min_time, max_time = [], []
for tran in path:
min_time.append(min_constraint_double(tran.guards[0]))
max_time.append(max_constraint_double(tran.guards[0], upper_guard))
# For each transition, maintain a mapping from logical time to the number of choices.
weight = dict()
for i in reversed(range(length)):
tran = path[i]
min_value, max_value = min_time[i], max_time[i]
weight[i] = dict()
if i == length - 1 or tran.reset:
for j in range(min_value, max_value + 1):
weight[i][j] = 1
else:
for j in range(min_value, max_value + 1):
weight[i][j] = 0
for k, w in weight[i + 1].items():
if k >= j:
weight[i][j] += w
# Now sample according to the weights
double_times = []
cur_time = 0
for i in range(length):
start_time = max(min_time[i], cur_time)
distr = []
for j in range(start_time, max_time[i] + 1):
distr.append(weight[i][j])
if sum(distr) == 0:
return None # sampling failed
cur_time = sample_distribution(distr) + start_time
double_times.append(cur_time)
if path[i].reset:
cur_time = 0
# Finally, change doubled time to fractions.
ltw = []
for i in range(length):
if double_times[i] % 2 == 0:
time = double_times[i] // 2
else:
time = double_times[i] // 2 + 0.5
ltw.append(TimedWord(path[i].action, time))
# Convert logical-timed word to delayed-timed word.
dtw = []
for i in range(length):
if i == 0 or path[i - 1].reset:
dtw.append(TimedWord(path[i].action, ltw[i].time))
else:
dtw.append(TimedWord(path[i].action,
ltw[i].time - ltw[i - 1].time))
return dtw