Experimental parser: always apply default transitions

tools/lexer_generator/nfa.py

 # Copyright 2013 the V8 project authors. All rights reserved.
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions are
 # met:
 #
 #     * Redistributions of source code must retain the above copyright
 #       notice, this list of conditions and the following disclaimer.
 #     * Redistributions in binary form must reproduce the above
 #       copyright notice, this list of conditions and the following
 #       disclaimer in the documentation and/or other materials provided
@@ skipping 113 matching lines @@
     value = self.__transitions[old_key]
     del self.__transitions[old_key]
     self.__transitions[new_key] = value
 
 class Nfa(Automaton):
 
   def __init__(self, encoding, start, end, nodes_created):
     super(Nfa, self).__init__(encoding)
     self.__start = start
     self.__end = end
-    self.__verify(nodes_created)
+    self.__node_count = nodes_created
+    self.__verify()
+
+  def node_count(self):
+    return self.__node_count
 
   def start_state(self):
     return self.__start
 
   def terminal_set(self):
     return set([self.__end])
 
-  def __verify(self, nodes_created):
+  def __verify(self):
     def f(node, count):
       node.post_creation_verify()
       return count + 1
     count = self.visit_all_states(f, 0)
-    assert count == nodes_created
+    assert count == self.__node_count
 
   @staticmethod
   def __gather_transition_keys(encoding, state_set):
     keys = set(chain(*map(lambda state: state.key_iter(), state_set)))
     keys.discard(TransitionKey.epsilon())
     return TransitionKey.disjoint_keys(encoding, keys)
 
   def __to_dfa(self, nfa_state_set, dfa_nodes):
     nfa_state_set = Automaton.epsilon_closure(nfa_state_set)
     # nfa_state_set will be a state in the dfa.
@@ skipping 18 matching lines @@
       f = lambda state: state.transition_state_iter_for_key(key)
       match_states = set(chain(*map(f, nfa_state_set)))
       transition_state = self.__to_dfa(match_states, dfa_nodes)
       dfa_nodes[name]['transitions'][key] = transition_state
     return name
 
   def compute_dfa(self):
     dfa_nodes = {}
     start_name = self.__to_dfa(set([self.__start]), dfa_nodes)
     return (start_name, dfa_nodes)