def return_vector(self, visitor):
listOfChildVectors = [
self.condition.accept(visitor),
self.nodeBlock.accept(visitor)
]
numOfTimes = int(round(sqrt(len(listOfChildVectors)))) + 1
for x in range(numOfTimes):
toBeAppended = deepcopy(listOfChildVectors)
listOfChildVectors = listOfChildVectors + toBeAppended
from ADT.Visitors.AssigmentComplexityVisitor import AssigmentComplexityVisitor
visitorComplexity = AssigmentComplexityVisitor(
enviromentWalkerContext())
from ADT.Visitors.RetrieveVariablesFromConditionVisitor import RetrieveVariablesFromConditionVisitor
variablesUsedInCondition = RetrieveVariablesFromConditionVisitor(
enviromentWalkerContext())
self.condition.accept(visitorComplexity)
self.condition.accept(variablesUsedInCondition)
visitor.currentArgumentVectorDependency = variablesUsedInCondition.currentArguments # TODO: CONSIDER LOOPS WITHOUT VARIABLES
listOfChildVectors += self.condition.accept(visitor)
numOfTimes = int(visitorComplexity.complexityOfCurrExpression**
NUM_COPY_SUBLIST) + 1
for x in range(numOfTimes):
toBeAppended = deepcopy(listOfChildVectors)
listOfChildVectors = listOfChildVectors + toBeAppended
return listOfChildVectors
def visit_binaryoperator(self, binaryOperator: BinaryOperator):
from ADT.Visitors.RetrieveVariablesFromConditionVisitor import RetrieveVariablesFromConditionVisitor
variablesUsedInCondition = RetrieveVariablesFromConditionVisitor(
enviromentWalkerContext())
if self.isInModifyingVariableState:
binaryOperator.leftOperand.accept(variablesUsedInCondition)
self.context.dataDependencies[
self.lastAssignedVariable.
variableName] += variablesUsedInCondition.currentArguments
self.context.dataDependencies[
self.lastAssignedVariable.variableName] = list(
set(self.context.dataDependencies[
self.lastAssignedVariable.variableName]))
variablesUsedInCondition.reset()
binaryOperator.rightOperand.accept(variablesUsedInCondition)
self.context.dataDependencies[
self.lastAssignedVariable.
variableName] += variablesUsedInCondition.currentArguments
self.context.dataDependencies[
self.lastAssignedVariable.variableName] = list(
set(self.context.dataDependencies[
self.lastAssignedVariable.variableName]))
binaryOperator.leftOperand.accept(self)
binaryOperator.rightOperand.accept(self)
def initialize(self, data):
self.resolverUtil = ResolverUtil()
self.currentVector = 0
self.currentNumOfTable = 0
self.currentNumOfRow = 0
self.argumentChangedVal = 0
self.currentHeuristicValue = 0
self.expressions = {}
self.currentHeuristics = []
self.currentVectors = []
self.currentHeuristicRow = []
self.currentVectorRow = []
self.rewarder = StaticRewardCalculator()
self.data = resolveRef(data, {})
self.mcdc = data
self.logicTable = None
self.rootAdtNode = {}
self.arguments = {}
self.argumentValues = {}
self.rootTreeAdtNode = None
self.listOfTables = []
self.listOfTableHeuristics = []
self.listOfTableVectors = []
self.context = enviromentWalkerContext()
self.getRootADTNode()
self.extractFunctionParams()
self.getLogicExpressionsFromMcDc()
self.parseLoadedJsonIntoTree()
self.createListOfMcDcTableRows()
def return_vector(self, visitor):
lists = []
from ADT.Visitors.AssigmentComplexityVisitor import AssigmentComplexityVisitor
visitorComplexity = AssigmentComplexityVisitor(enviromentWalkerContext())
from ADT.Visitors.RetrieveVariablesFromConditionVisitor import RetrieveVariablesFromConditionVisitor
variablesUsedInCondition = RetrieveVariablesFromConditionVisitor(enviromentWalkerContext())
self.value.accept(visitorComplexity)
if isinstance(self.variable, VariableNode):
self.value.accept(variablesUsedInCondition)
visitor.currentArgumentVectorDependency = variablesUsedInCondition.currentArguments + [self.variable.variableName]
lists += self.make_vector(visitor)
lists += self.value.accept(visitor)
numOfTimes = int(visitorComplexity.complexityOfCurrExpression ** NUM_COPY_SUBLIST) + 1
for x in range(numOfTimes):
toBeAppended = deepcopy(lists)
lists = lists + toBeAppended
return lists
def prepareVectorsForRowsConv(self):
for table in self.listOfTables:
tableRows = []
# Extract values for each column according to one row
for row in table:
dictForRow = self.mergeDictsInRow(row)
self.vectorizationVisitor = SampleVisitorEnv(
enviromentWalkerContext(), dictForRow, self.expressions)
mainNode = self.rootTreeAdtNode.accept(
self.vectorizationVisitor)
tableRows.append(mainNode)
self.listOfTableVectors.append(tableRows)
def createVectorsForRows(self):
for table in self.listOfTables:
tableRows = []
# Extract values for each column according to one row
for row in table:
dictForRow = self.mergeDictsInRow(row)
dataDependencyVisitor = DataDependenciesVisitor(
enviromentWalkerContext(), dictForRow, self.expressions)
self.rootTreeAdtNode.accept(dataDependencyVisitor)
self.vectorizationVisitor = VectorizationVisitor(
dataDependencyVisitor.context, dictForRow, self.arguments,
self.expressions)
lists = self.rootTreeAdtNode.accept(self.vectorizationVisitor)
lists = [x for x in lists if x != []]
numOfTimes = int(round(len(lists))**(1 / 4)) + 1
for x in range(numOfTimes):
toBeAppended = deepcopy(lists)
lists = lists + toBeAppended
tableRows.append(lists)
self.listOfTableVectors.append(tableRows)
def reset(self):
self.context = enviromentWalkerContext()
def reset(self):
self.context = enviromentWalkerContext()
self.embedding = 0
self.functionName = ""
self.numOfStaticRecursionCalls = 0
self.currentArgumentVectorDependency = []
def reset(self):
self.context = enviromentWalkerContext()
self.currentArguments = []
import pickle
from Environment.enviroment import Enviroment
from Environment.enviromentWalkerRedLabel import enviromentWalkerContext
from Vectorizer.Sample import SampleVisitor
from Vectorizer.train import learn_vectors
# Creates the embeddings for the given dataset we specified in the Enviroment class
env = Enviroment()
m = 0
Samples = []
while m < len(env.listOfFiles):
env.prepareNextFile()
for table in env.listOfTables:
tableRows = []
# Extract values for each column according to one row
for row in table:
dictForRow = env.mergeDictsInRow(row)
sampleVisitor = SampleVisitor(enviromentWalkerContext(),
dictForRow, env.expressions,
env.rootTreeAdtNode.name)
lists = sampleVisitor.traverse_tree(env.rootTreeAdtNode)
lists = [x for x in lists if x != []]
Samples += lists
m += 1
embed_file = open('vectors_nextDate.pkl', 'wb')
lists = learn_vectors(Samples, 'Vectorizer/logs')
pickle.dump(lists, embed_file)
embed_file.close()
def prepareVectorsForTablesConvWithCov(self):
for table in self.listOfTables:
self.vectorizationVisitor = SampleVisitorEnvWithConv(
enviromentWalkerContext(), self.rootTreeAdtNode.name)
mainNode = self.rootTreeAdtNode.accept(self.vectorizationVisitor)
self.listOfTableVectors.append(mainNode)