A new algorithm for exact reduction of incompletely specified finite state machines
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- TL;DR
- We propose a new exact algorithm for reducing states in incompletely specified finite state machines, avoiding the performance bottlenecks of traditional compatible-set enumeration methods.
- Problem
- Traditional algorithms for state reduction rely on enumerating compatible sets, meaning their performance heavily depends on the total number of such sets.
- Method
- Instead of enumerating compatible sets, our algorithm adapts well-known finite state machine identification techniques from computer science that have not been applied to this problem before.
- Results
- Experiments on a set of hard problems show that our algorithm is much more efficient than both explicit and implicit approaches based on compatible-set enumeration.
- Contributions
- We prove that the algorithm is exact, provide a complexity analysis identifying special cases with polynomial time bounds, and validate these bounds empirically.
- Limitations
- Not specified in the abstract.
- Takeaways
- This work introduces a more efficient, exact approach to finite state machine reduction by leveraging established identification techniques rather than compatible-set enumeration.
- Applications
- Computer-aided design of integrated circuits and systems.
- Topics
- Finite State Machines, State Reduction, Algorithms, Computer-Aided Design
- For industry
- Semiconductor and Integrated Circuit Design
- Why it matters
- Not specified in the abstract.
Abstract
We propose a new algorithm for the problem of state reduction in incompletely specified finite state machines. Unlike the most commonly used algorithms for this problem, our approach is not based on the enumeration of compatible sets, and, therefore, its performance is not dependent on its number. Instead, the algorithm uses techniques for finite state machine identification that are well known in the computer science literature, but have never been applied to this problem. We prove that the algorithm is exact and present results that show that, in a set of hard problems, it is much more efficient than both the explicit and implicit approaches based on the enumeration of compatible sets. We also present a complexity analysis for the special cases where worst case polynomial time bounds can be obtained and present experiments that validate empirically the bounds obtained.