Enhancing FSM traversal by temporary re-encoding

Synthesis and optimization of large finite-state machines has improved dramatically over the last few years with the introduction and rapid improvement of symbolic-state manipulation techniques. The algorithms efficiently visit each reachable state in the machine while computing and storing information about these states. We propose a new technique for improving the efficacy of traversal algorithms: re-encoding the states of the machine to more efficiently represent state sets or state transitions, or to more efficiently compute the next set of states. Our technique can be embedded in existing traversal algorithms. Experiments reveal that re-encoding can indeed reduce the time and/or space required for traversal.