コード例 #1
0
ファイル: efsm_examplei-li.py プロジェクト: RINSMQ/project
def example():
    """This example show how to create a marked Laurie state machine"""
##################################################
#select a example here
#     currentdir = os.curdir
#     imagedir = os.path.join(currentdir, "..\..\subjects")
#     imagefile = os.path.join(imagedir, "test.txt")
#     print imagefile

    modelfiledir = '../../subjects/'
#    currentdir = os.path.dirname(__file__)


#imagedir = os.path.join(currentdir, "images")
#    modelfile="test.txt"

#    modelfile="ntscd_example.txt"
#    modelfile="sm3.txt"
#    modelfile="fairnessEG.txt"
#    modelfile="kellysample.txt"
    modelfile="EFSM_ATM.txt"    #by zhao
#    modelfile="EFSM_ATM_noexit.txt"
#    modelfile="EFSM_Cashier.txt"
#    modelfile="EFSM_Cashier_noexit.txt"
#    modelfile="EFSM_CruiseControl.txt"
#    modelfile="EFSM_FuelPump.txt"
#    modelfile="EFSM_FuelPump_noexit.txt"
#    modelfile="EFSM_INRES.txt"
#    modelfile="EFSM_INRES_noexit.txt"
#    modelfile="EFSM_Lift.txt"
#    modelfile="EFSM_PrinTok.txt"
#    modelfile="EFSM_SimplifiedPhone.txt"
#    modelfile="EFSM_SimplifiedPhone_noexit.txt"
#    modelfile="EFSM_TCP.txt"
#    modelfile="EFSM_TCSbin.txt"
#    modelfile="EFSM_TCSbin_EXIT.txt"
#    modelfile="EFSM_VendingMachine.txt"
#    modelfile="EFSM_VendingMachine_noexit.txt"
##################################################
#initialize the model and dependence of SM
    inputfile = modelfiledir+modelfile
    SM=EFSM.efsmFromFile(inputfile)
#    print "%s has %s states and  %s transitions" %(SM.name, len(SM.stateList), len(SM.transitionList))
#    print '\transiton\n', SM.transitionList

##################################################
#view the model
#create Laurie SM, with marked transitions
    states=[]
    for s in SM.stateList:
        if s.name=='START':
            states.append(LSM.State(s.name, True))
        else:
            states.append(LSM.State(s.name))

    transitions=[]
    for tran in SM.transitionList:
        srcState=[state for state in states if state.name == tran.src.name].pop()
        tgtState=[state for state in states if state.name == tran.tgt.name].pop()
        transitions.append(LSM.Transition(tran.name, srcState, tgtState, True))

    EFSMGraph = LSM.State_Machine(states, transitions)
    EFSMGraph.visualize()
##################################################
#initialize the dependence of model
    EFSM.initEFSM(SM)

##################################################
#TEST
#    print SM.stateTransitiveSuccessor(SM.state('START'))
#    print SM.ntscdSuccessor(SM.transition('TS12'))
#    print SM.maxPathDict[SM.transition('TS11').name]
#   print SM.findSuccSinkPath(SM.transition('TS2'))
#     for transition in SM.transitionList:
#         print transition, ":\n"
# #        print SM.findMaxPath(transition)
#         print SM.maxPathDict[transition.name]
#         print "\n"
    # print SM.findSuccMaxPath(SM.transition('T3'))
    # print SM.maxPathDict[SM.transition('T2').name]

##################################################
# #output variables for each transition
#     ofile=open(SM.name+"_variables_list.txt", "w") 
#     vSet=set()
#     for tran in SM.transitionList:
# #       {eventVdef:vlist, condVuse:vlist, actionVdef:vlist, actionVuse,vlist}
#         for x in ["eventVdef", "condVuse", "actionVdef", "actionVuse"]:
#             ofile.write(tran.name+'\t'+x+':\t')
#             for y in SM.tranVarDict[tran.name][x]:
#                 ofile.write(y+'\t')
#                 vSet.add(y)
#             ofile.write('\n')

#     ofile.write("\ntotal variables: "+str(len(vSet))+'\n')
#     for v in vSet:
#         ofile.write(v+', ')
#     ofile.close()

##################################################
#generate dependence graph
#    print 'generate the dependence graph...'

#    SMDG=SM.makeDependenceGraph('DATA', 'NTSCD')
#    SMDG=SM.makeDependenceGraph('DATA', 'NTICD')
#    SMDG=SM.makeDependenceGraph('DATA', 'UNTICD')
#    SMDG.view()    # view the dependence graph

    for cd in ['NTICD', 'NTSCD', 'UNTICD']:
        SMDG=SM.makeDependenceGraph('DATA', cd)
        SMDG.view()    # view the dependence graph
    

# ##################################################
# #define a slicing criterion here
    criterion=SM.transition('T7')


# ##################################################
#generate the dependence graph wrt the criterion
    subDG=SMDG.subBWGraphwrtNode(criterion)
    subDG.view(criterion) # view the subdependence graph

#create Laurie SM, with marked transitions
    states=[]
    for s in SM.stateList:
        if s.name=='START':
            states.append(LSM.State(s.name, True))
        else:
            states.append(LSM.State(s.name))

    transitions=[]
    for tran in SM.transitionList:
        srcState=[state for state in states if state.name == tran.src.name].pop()
        tgtState=[state for state in states if state.name == tran.tgt.name].pop()
        if tran in subDG.nodeList:
            transitions.append(LSM.Transition(tran.name, \
                                                 srcState, tgtState, True))
        else:
            transitions.append(LSM.Transition(tran.name, \
                                                 srcState, tgtState, False))

    SMGraph=LSM.State_Machine(states,transitions)   # added by zhao on 21.04.2009
    SMGraph.visualize()     # added by zhao on 21.04.2009
コード例 #2
0
ファイル: profile_example.py プロジェクト: RINSMQ/project
def example():
    """This example show how to create a marked Laurie state machine"""
##################################################
#select a example here
#     currentdir = os.curdir
#     imagedir = os.path.join(currentdir, "..\..\subjects")
#     imagefile = os.path.join(imagedir, "test.txt")
#     print imagefile

    modelfiledir = '../../subjects/'
#    currentdir = os.path.dirname(__file__)


#imagedir = os.path.join(currentdir, "images")

#    modelfile="ntscd_example.txt"
#    modelfile="sm3.txt"
#    modelfile="fairnessEG.txt"
#    modelfile="kellysample.txt"
#    modelfile="EFSM_ATM.txt"
#    modelfile="EFSM_ATM_noexit.txt"
#    modelfile="EFSM_Cashier.txt"
#    modelfile="EFSM_Cashier_noexit.txt"
#    modelfile="EFSM_CruiseControl.txt"
#    modelfile="EFSM_FuelPump.txt"
#    modelfile="EFSM_FuelPump_noexit.txt"
#    modelfile="EFSM_INRES_noexit.txt"
#    modelfile="EFSM_Lift.txt"
    modelfile="EFSM_PrinTok.txt"
#    modelfile="EFSM_SimplifiedPhone.txt"
#    modelfile="EFSM_SimplifiedPhone_noexit.txt"
#    modelfile="EFSM_VendingMachine.txt"
#    modelfile="EFSM_VendingMachine_noexit.txt"
##################################################
#initialize the model and dependence of SM
    inputfile = modelfiledir+modelfile
    SM=EFSM.efsmFromFile(inputfile)

# #view the model
# #create Laurie SM, with marked transitions
#     states=[]
#     for s in SM.stateList:
#         if s.name=='START':
#             states.append(LSM.State(s.name, True))
#         else:
#             states.append(LSM.State(s.name))

#     transitions=[]
#     for tran in SM.transitionList:
#         srcState=[state for state in states if state.name == tran.src.name].pop()
#         tgtState=[state for state in states if state.name == tran.tgt.name].pop()
#         transitions.append(LSM.Transition(tran.name, srcState, tgtState, True))

#     EFSMGraph = LSM.State_Machine(states, transitions)
#     EFSMGraph.visualize()

#initialize the dependence of model
    EFSM.initEFSM(SM)

##################################################
#TEST
#    print SM.ntscdSuccessor(SM.transition('T12'))
#    print SM.maxPathDict[SM.transition('T4').name]
#   print SM.findSuccSinkPath(SM.transition('T2'))
#     for transition in SM.transitionList:
#         print transition, ":\n"
# #        print SM.findMaxPath(transition)
#         print SM.maxPathDict[transition.name]
#         print "\n"

#     ofile=open("test.txt", "w")
#     for transition in SM.transitionList:
#         ofile.write(transition.name+'\t'+ str(SM.maxPathDict[transition.name])+'\n')
#     ofile.close()
#     sum=0
#     for transition in SM.transitionList:
#          x=len(SM.maxPathDict[transition.name])
#          sum += x
#          print x
#     print 'sum', sum



# #count slibling transition and their successors
#     tempSet=set()
#     for transition in SM.transitionList:
#         if SM.transitionSibling(transition):
#             tempSet.add(transition)
#     for transition in tempSet.copy():
#         for t in SM.succDict[transition.name]:
#             tempSet.add(t)
#     print('lenth of set is ', len(tempSet))



##################################################
#select the control dependence here and generate 
#the dependence graph
    print 'generate the dependence graph...'