#!/usr/bin/python # This utility reads the given file and generates a DFA graph of all the possible state transitions. # This interprets the signals as states. import json from pprint import pprint from samba.dcerpc.dfs import DFS_GLOBAL_HIGH_PRIORITY_CLASS outputJsonFile = open('output.json', 'r') outputJson = json.load(outputJsonFile) outputJsonFile.close() lastItem = None transitions = dict() for item in outputJson: if (lastItem): # A transition from lastItem to item.type if (not transitions.has_key(lastItem)): transitions[lastItem] = dict() transitions[lastItem][item['type']] = 1 lastItem = item['type'] # Moore reduction here itemToKPartition = dict() kPartitionToItems = dict() f = open('dfa.dot', 'w') f.write("digraph G {\n") for fromItem in transitions.keys(): # We will try to do minimization here also. toItems = transitions[fromItem].keys() for toItem in toItems: f.write(" \"" + fromItem + "\"->\"" + toItem + "\";\n") k = ":".join(sorted(toItems)) # All fromItems in the same kPartition are kEquivalent, because their outputs are the same. itemToKPartition[fromItem] = k if (not kPartitionToItems.has_key(k)): kPartitionToItems[k] = [] kPartitionToItems[k].append(fromItem) print kPartitionToItems f.write("}\n") f.close() f_reduced = open('dfa_reduced.dot', 'w') f_reduced.write("digraph G {\n") transitions_reduced = dict() # Reducing. One iteration is enough. for fromItemRaw in transitions.keys(): fromItemK = itemToKPartition[fromItemRaw] fromItem = ":".join(sorted(kPartitionToItems[fromItemK])) print fromItem toItemsRaw = transitions[fromItemRaw].keys() toItems = dict() for toItemRaw in toItemsRaw: toItemK = itemToKPartition[toItemRaw] toItemKey = ":".join(sorted(kPartitionToItems[toItemK])) toItems[toItemKey] = 1 transitions_reduced[fromItem] = toItems.keys() for fromItem in transitions_reduced.keys(): # We will try to do minimization here also. toItems = transitions_reduced[fromItem] for toItem in toItems: f_reduced.write(" \"" + fromItem + "\"->\"" + toItem + "\";\n") f_reduced.write("}\n") f_reduced.close()