EXACT AND HEURISTIC ALGORITHMS FOR THE MINIMIZATION OF INCOMPLETELY SPECIFIED STATE MACHINES

In this paper me present two exact algorithms for state minimization o f FSM's. Our results prove that exact state minimization is feasible f or a large class of practical examples, certainly including most hand- designed FSM's. We also present heuristic algorithms, that can handle large, machine-generated, FSM's. The possibly many different reduced m achines with the same number of states have different implementation c osts. We discuss two steps of the minimization procedure, called state mapping and solution shrinking, that have received little prior atten tion in the literature, though they play a significant role in deliver ing an optimally implemented reduced machine. We also introduce an alg orithm whose main virtue is the ability to cope with very general cost functions, while Providing high performance.