def initializeObservationTable(self):
self.log.info("Initialization of the observation table")
self.suffixes = []
self.D = []
# Create the S and SA
self.S = []
self.SA = []
self.initialD = []
# fullfill D with the dictionary
for entry in self.getInputDictionary():
letter = DictionarySymbol(entry)
mq = MembershipQuery([letter])
self.addWordInD(mq)
self.initialD.append(mq)
# self.D.append(letter)
# self.suffixes.append(letter)
# Initialize the observation table
emptyMQ = MembershipQuery([EmptySymbol()])
self.addWordInS(emptyMQ)
def preloadCacheEntry(self, data, vocabulary):
tab = data.split(" > ")
msgSymbols = tab[0]
mqSymbols = msgSymbols.split(",")
symbols = []
for mqSymbol in mqSymbols:
symbol = vocabulary.getSymbolByName(mqSymbol)
if symbol is not None:
symbols.append(symbol)
mq = MembershipQuery(symbols)
msgResult = tab[1]
tmp = msgResult.split(",")
symbolsResult = []
for t in tmp:
symbol = vocabulary.getSymbolByName(t)
if symbol is not None:
symbolsResult.append(symbol)
self.cacheResult(mq, symbolsResult)
def findCounterExample(self, mmstd, inputSymbols, cache):
self.log.info("=====================================================")
self.log.info("Find a counterexample which invalids the given MMSTD")
self.log.info("=====================================================")
inputDictionary = []
for entry in inputSymbols:
letter = DictionarySymbol(entry)
inputDictionary.append(letter)
self.log.info("The vocabulary contains: {0}".format(str(letter)))
# -----------------------------------------------------------------------
# FIRST WE COMPUTE WHICH WILL WE MAKE !
# -----------------------------------------------------------------------
# This our plan to find same
# STEP 1 : Estimate the maximum number of states (m) in the correct implementation
# of the FSM (DONE PREVISOULY AND TRANSMITED THROUGH PARAM self.maxsize
# STEP 2 : Construct the characterization set W for [MMSTD]
# STEP 3:
# (a) Construct the "testing tree" for MMSTD
# (b) Generate the transition cover set P from the testing tree
# STEP 4 : Construct set Z from W and m
# STEP 5 : We have the list of so desired test cases = P.Z
# STEP 2:
# - Construct a sequence of k-equivalence partitions of the states of MMSTD:
# Find all the couples of states
couples = []
states = mmstd.getAllStates()
W = []
self.log.info("The MMSTD has " + str(len(states)) + " states")
self.log.info("A number of " + str(self.m) + " states is estimated.")
for state in states:
for state2 in states:
if state != state2:
found = False
for (s1, s2) in couples:
if not ((s1 == state) and (s2 == state2) or
((s1 == state2) and (s2 == state))):
found = True
if not found:
couples.append((state, state2))
self.log.info("A number of " + str(len(couples)) +
" couples was found")
for (state1, state2) in couples:
self.log.info("Search a distinguish string between " +
state1.getName() + " and " + state2.getName())
z = MembershipQuery([EmptySymbol()])
mqToTest = deque([])
for letter in inputDictionary:
mqToTest.append(
z.getMQSuffixedWithMQ(MembershipQuery([letter])))
lastIndiguishableZ = z
distinguishableZ = z
done = False
i = 0
while not done:
mq = mqToTest.popleft()
if i > self.m * self.m:
break
self.log.info("Can we distinguish with MQ = " + str(mq))
if not self.canWeDistinguishStates(mmstd, mq, state1, state2):
done = False
lastIndiguishableZ = mq
for letter in inputDictionary:
z = mq.getMQSuffixedWithMQ(MembershipQuery([letter]))
mqToTest.append(z)
else:
done = True
distinguishableZ = mq
i = i + 1
self.log.info(
"FOUND: the following distinguish them: {0} last which doesn't is {1}"
.format(str(distinguishableZ), str(lastIndiguishableZ)))
W.append(distinguishableZ)
self.log.info("=================================")
self.log.info("W = " + str(W))
self.log.info("=================================")
# Execute STEP 3 : We compute P
# init P = {E, ...}
currentMQ = MembershipQuery([EmptySymbol()])
P = [currentMQ]
openMQ = deque([currentMQ])
closeMQ = []
statesSeen = [mmstd.getInitialState()]
while len(openMQ) > 0:
self.log.info("Compute P, ...")
mq = openMQ.popleft()
tmpstatesSeen = []
for letter in inputDictionary:
z = mq.getMQSuffixedWithMQ(MembershipQuery([letter]))
self.log.debug(
"Get output trace if we execute the MMSTD with " +
str(z.getSymbols()))
(trace,
outputState) = mmstd.getOutputTrace(mmstd.getInitialState(),
z.getSymbols())
if outputState in statesSeen:
# we close this one
self.log.info("Adding " + str(z) + " in closeMQ")
closeMQ.append(z)
else:
tmpstatesSeen.append(outputState)
self.log.info("Adding " + str(z) + " in closeMQ")
closeMQ.append(z)
# still open
openMQ.append(z)
statesSeen.extend(tmpstatesSeen)
P.extend(closeMQ)
# STEP 4 : We compute Z
# it follows the formula Z= W U (X^1.W) U .... U (X^(m-1-n).W) U (W^(m-n).W)
self.log.info("Computing Z:")
Z = []
# First we append W in Z
for w in W:
Z.append(w)
v = self.m - len(states)
if v < 0:
v = 0
mqInputs = []
for input in inputDictionary:
mqInputs.append(MembershipQuery([input]))
X = dict()
X[0] = W
for i in range(1, v + 1):
self.log.info("Computing X^{0}: ".format(str(i)))
self.log.info("MQ INputs: {}".format(str(len(mqInputs))))
self.log.info("W: {}".format(str(len(W))))
X[i] = []
previousX = X[i - 1]
self.log.info(previousX)
for x in previousX:
X[i].extend(x.multiply(mqInputs))
for w in W:
for xi in X[i]:
if not xi in Z:
Z.append(xi)
else:
self.log.warn(
"Impossible to add X[{0}] = {1} in Z, it already exists"
.format(str(i), str(xi)))
for z in Z:
self.log.info("z = {0}".format(str(z)))
# STEP 5 : We have the list of so desired test cases T = P.Z
T = []
for p in P:
T.extend(p.multiply(Z))
self.log.info("Tests cases are: ")
for t in T:
self.log.info("=> {0}".format(str(t)))
self.log.info(
"----> Compute the responses to the the tests over our model and compare them with the real one"
)
i_test = 0
# We compute the response to the different tests over our learning model and compare them with the real one
for test in T:
i_test = i_test + 1
# Compute our results
(traceTest,
stateTest) = mmstd.getOutputTrace(mmstd.getInitialState(),
test.getSymbols())
# Verify the request is not in the cache
cachedValue = cache.getCachedResult(test)
if cachedValue is None:
# Compute real results
if self.resetScript != "":
os.system("sh " + self.resetScript)
self.log.debug("=====================")
self.log.debug("Execute test {0}/{1}: {2}".format(
str(i_test), str(len(T)), str(test)))
self.log.debug("=====================")
isMaster = not self.communicationChannel.isServer()
testedMmstd = test.toMMSTD(mmstd.getVocabulary(),
isMaster) # TODO TODO
oracle = NetworkOracle(self.communicationChannel,
isMaster) # TODO TODO is master ??
oracle.setMMSTD(testedMmstd)
oracle.start()
while oracle.isAlive():
time.sleep(0.01)
oracle.stop()
if isMaster:
resultQuery = oracle.getGeneratedOutputSymbols()
else:
resultQuery = oracle.getGeneratedInputSymbols()
cache.cacheResult(test, resultQuery)
else:
resultQuery = cachedValue
mqOur = MembershipQuery(traceTest)
mqTheir = MembershipQuery(resultQuery)
if not mqOur.isStrictlyEqual(mqTheir):
self.log.info("========================")
self.log.info("We found a counter example")
self.log.info("========================")
self.log.info("TEST: {0}".format(str(test)))
self.log.info("OUR: {0}".format(str(mqOur)))
self.log.info("THEIR: {0}".format(str(mqTheir)))
return test
else:
self.log.info("========================")
self.log.info("Not a counter example")
self.log.info("========================")
return None
def findCounterExample(self, mmstd, inputSymbols, cache):
self.log.info("=====================================================")
self.log.info("Find a counterexample which invalids the given MMSTD")
self.log.info("=====================================================")
inputDictionary = []
for entry in inputSymbols:
letter = DictionarySymbol(entry)
inputDictionary.append(letter)
self.log.info("The vocabulary contains: {0}".format(str(letter)))
# -----------------------------------------------------------------------
# FIRST WE COMPUTE WHICH WILL WE MAKE !
# -----------------------------------------------------------------------
# This our plan to find same
# STEP 1 : Estimate the maximum number of states (m) in the correct implementation
# of the FSM (DONE PREVISOULY AND TRANSMITED THROUGH PARAM self.maxsize
# STEP 2 : Construct the characterization set W for [MMSTD]
# STEP 3:
# (a) Construct the "testing tree" for MMSTD
# (b) Generate the transition cover set P from the testing tree
# STEP 4 : Construct set Z from W and m
# STEP 5 : We have the list of so desired test cases = P.Z
# STEP 2:
# - Construct a sequence of k-equivalence partitions of the states of MMSTD:
# Find all the couples of states
couples = []
states = mmstd.getAllStates()
W = []
self.log.info("The MMSTD has " + str(len(states)) + " states")
self.log.info("A number of " + str(self.m) + " states is estimated.")
for state in states:
for state2 in states:
if state != state2:
found = False
for (s1, s2) in couples:
if not ((s1 == state) and (s2 == state2) or ((s1 == state2) and (s2 == state))):
found = True
if not found:
couples.append((state, state2))
self.log.info("A number of " + str(len(couples)) + " couples was found")
for (state1, state2) in couples:
self.log.info("Search a distinguish string between " + state1.getName() + " and " + state2.getName())
z = MembershipQuery([EmptySymbol()])
mqToTest = deque([])
for letter in inputDictionary:
mqToTest.append(z.getMQSuffixedWithMQ(MembershipQuery([letter])))
lastIndiguishableZ = z
distinguishableZ = z
done = False
i = 0
while not done:
mq = mqToTest.popleft()
if i > self.m * self.m:
break
self.log.info("Can we distinguish with MQ = " + str(mq))
if not self.canWeDistinguishStates(mmstd, mq, state1, state2):
done = False
lastIndiguishableZ = mq
for letter in inputDictionary:
z = mq.getMQSuffixedWithMQ(MembershipQuery([letter]))
mqToTest.append(z)
else:
done = True
distinguishableZ = mq
i = i + 1
self.log.info("FOUND: the following distinguish them: {0} last which doesn't is {1}".format(str(distinguishableZ), str(lastIndiguishableZ)))
W.append(distinguishableZ)
self.log.info("=================================")
self.log.info("W = " + str(W))
self.log.info("=================================")
# Execute STEP 3 : We compute P
# init P = {E, ...}
currentMQ = MembershipQuery([EmptySymbol()])
P = [currentMQ]
openMQ = deque([currentMQ])
closeMQ = []
statesSeen = [mmstd.getInitialState()]
while len(openMQ) > 0:
self.log.info("Compute P, ...")
mq = openMQ.popleft()
tmpstatesSeen = []
for letter in inputDictionary:
z = mq.getMQSuffixedWithMQ(MembershipQuery([letter]))
self.log.debug("Get output trace if we execute the MMSTD with " + str(z.getSymbols()))
(trace, outputState) = mmstd.getOutputTrace(mmstd.getInitialState(), z.getSymbols())
if outputState in statesSeen:
# we close this one
self.log.info("Adding " + str(z) + " in closeMQ")
closeMQ.append(z)
else:
tmpstatesSeen.append(outputState)
self.log.info("Adding " + str(z) + " in closeMQ")
closeMQ.append(z)
# still open
openMQ.append(z)
statesSeen.extend(tmpstatesSeen)
P.extend(closeMQ)
# STEP 4 : We compute Z
# it follows the formula Z= W U (X^1.W) U .... U (X^(m-1-n).W) U (W^(m-n).W)
self.log.info("Computing Z:")
Z = []
# First we append W in Z
for w in W:
Z.append(w)
v = self.m - len(states)
if v < 0:
v = 0
mqInputs = []
for input in inputDictionary:
mqInputs.append(MembershipQuery([input]))
X = dict()
X[0] = W
for i in range(1, v + 1):
self.log.info("Computing X^{0}: ".format(str(i)))
self.log.info("MQ INputs: ".format(str(len(mqInputs))))
self.log.info("W: ".format(str(len(W))))
X[i] = []
previousX = X[i - 1]
self.log.info(previousX)
for x in previousX:
X[i].extend(x.multiply(mqInputs))
for w in W:
for xi in X[i]:
if not xi in Z:
Z.append(xi)
else:
self.log.warn("Impossible to add X[{0}] = {1} in Z, it already exists".format(str(i), str(xi)))
for z in Z:
self.log.info("z = {0}".format(str(z)))
# STEP 5 : We have the list of so desired test cases T = P.Z
T = []
for p in P:
T.extend(p.multiply(Z))
self.log.info("Tests cases are: ")
for t in T:
self.log.info("=> {0}".format(str(t)))
testsResults = dict()
self.log.info("----> Compute the responses to the the tests over our model and compare them with the real one")
i_test = 0
# We compute the response to the different tests over our learning model and compare them with the real one
for test in T:
i_test = i_test + 1
# Compute our results
(traceTest, stateTest) = mmstd.getOutputTrace(mmstd.getInitialState(), test.getSymbols())
# Verify the request is not in the cache
cachedValue = cache.getCachedResult(test)
if cachedValue is None:
# Compute real results
if self.resetScript != "":
os.system("sh " + self.resetScript)
self.log.debug("=====================")
self.log.debug("Execute test {0}/{1}: {2}".format(str(i_test), str(len(T)), str(test)))
self.log.debug("=====================")
isMaster = not self.communicationChannel.isServer()
testedMmstd = test.toMMSTD(mmstd.getVocabulary(), isMaster) # TODO TODO
oracle = NetworkOracle(self.communicationChannel, isMaster) # TODO TODO is master ??
oracle.setMMSTD(testedMmstd)
oracle.start()
while oracle.isAlive():
time.sleep(0.01)
oracle.stop()
if isMaster:
resultQuery = oracle.getGeneratedOutputSymbols()
else:
resultQuery = oracle.getGeneratedInputSymbols()
cache.cacheResult(test, resultQuery)
else:
resultQuery = cachedValue
mqOur = MembershipQuery(traceTest)
mqTheir = MembershipQuery(resultQuery)
if not mqOur.isStrictlyEqual(mqTheir):
self.log.info("========================")
self.log.info("We found a counter example")
self.log.info("========================")
self.log.info("TEST: {0}".format(str(test)))
self.log.info("OUR: {0}".format(str(mqOur)))
self.log.info("THEIR: {0}".format(str(mqTheir)))
return test
else:
self.log.info("========================")
self.log.info("Not a counter example")
self.log.info("========================")
return None
def computeAutomata(self):
wordAndStates = []
startState = None
idState = 0
idTransition = 0
states = []
self.log.info("Compute the automata...")
# Create the states of the automata
uniqueRowsInS = self.getUniqueRowsInS()
for (w, r) in uniqueRowsInS:
self.log.info("The row with word {0} is unique !".format(str(w)))
# We create a State for each unique row
nameState = self.appendValuesInRow(r)
self.log.info("Create state: {0}".format(nameState))
currentState = NormalState(idState, nameState)
states.append(currentState)
wordAndStates.append((w, currentState))
# Is it the starting state (wordS = [EmptySymbol])
if startState is None and w == MembershipQuery([EmptySymbol()]):
startState = currentState
self.log.info("Its the starting state")
idState = idState + 1
self.log.debug("Create the transition of the automata")
# Create the transitions of the automata
for (word, state) in wordAndStates:
self.log.debug("Working on state: {0}".format(str(state.getName())))
for symbol in self.initialD:
# retrieve the value:
dicValue = self.observationTable[symbol]
value = dicValue[word]
# search for the output state
mq = word.getMQSuffixedWithMQ(symbol)
self.log.debug("> What happen when we send " + str(symbol) + " after " + str(word))
self.log.debug(">> " + str(mq))
for wordSandSA in self.getSandSAWords():
self.log.info("IS " + str(wordSandSA) + " eq " + str(mq))
if wordSandSA == mq:
self.log.info("YES its equal")
rowOutputState = self.getRowOfObservationTable(wordSandSA)
outputStateName = self.appendValuesInRow(rowOutputState)
self.log.debug("rowOutputState = " + str(rowOutputState))
self.log.debug("outputStateName = " + str(outputStateName))
# search for the state having this name:
outputState = None
self.log.info("Search for the output state: {0}".format(outputStateName))
for (w2, s2) in wordAndStates:
if s2.getName() == outputStateName:
outputState = s2
self.log.info(" == " + str(s2.getName()))
else:
self.log.info(" != " + str(s2.getName()))
if outputState is not None:
inputSymbol = symbol.getSymbolsWhichAreNotEmpty()[0]
self.log.info("We create a transition from " + str(state.getName()) + "=>" + str(outputState.getName()))
self.log.info(" input: {0}".format(str(inputSymbol)))
self.log.info(" output: {0}".format(str(value)))
transition = SemiStochasticTransition(idTransition, "Transition " + str(idTransition), state, outputState, inputSymbol)
transition.addOutputSymbol(value, 100, 1000)
state.registerTransition(transition)
idTransition = idTransition + 1
else:
self.log.error("<!!> Impossible to retrieve the output state named " + str(s2.getName()))
if startState is not None:
self.log.info("An infered automata has been computed.")
self.inferedAutomata = MMSTD(startState, self.dictionary)
for state in states:
self.inferedAutomata.addState(state)
self.log.info(self.inferedAutomata.getDotCode())