Probabilistic Model Checking via Families of Deterministic and Unambiguous Finite Automata

2026-06-20

AI Summary

This work investigates the applicability of Families of DFAs (FDFAs) in probabilistic model checking and proposes more compact representations for ω-regular languages. For discrete-time Markov chains, it presents the first polynomial-time probabilistic model-checking algorithm based on FDFAs. The study further introduces a novel non-deterministic yet unambiguous automaton model, termed FUFA, which offers exponentially more succinct representations than both FDFAs and unambiguous Büchi automata. Key contributions include a single-exponential translation from LTL to FUFA—significantly improving upon the known double-exponential lower bound for LTL-to-FDFA translations—and enabling efficient probabilistic verification for specifications given as FDFAs or certain classes of FUFAs.

Abstract

Families of deterministic finite automata (FDFA) have been introduced as a concise automaton model that characterizes $ω$-regular languages by processing their ultimately periodic words. FDFA are known to enjoy many good properties and can be exponentially more succinct than deterministic $ω$-automata with Rabin, Streett or parity acceptance. This paper addresses two main questions: (1) Are FDFA suitable for probabilistic model checking purposes? and (2) Is it possible to obtain an even more compact representation of $ω$-regular languages by allowing the components of an FDFA to be unambiguous instead of deterministic? Question (1) is answered in the affirmative by presenting the first polynomial-time algorithm for computing the probability that a discrete-time Markov chain satisfies an $ω$-regular property represented as an FDFA. Question (2) is motivated by the fact that unambiguous finite automata may require exponentially fewer states than deterministic ones. This paper introduces a model of families of unambiguous finite automata (FUFA) that captures the class of $ω$-regular languages. FUFA can be exponentially more succinct than both FDFA and unambiguous Büchi automata, and there is a single-exponential translation from linear temporal logic (LTL) to FUFA. This stands in contrast to a double-exponential lower bound for the translation from LTL to FDFA. Moreover, the polynomial-time probabilistic model checking algorithm for discrete-time Markov chains against FDFA-specifications is extended to the case where the property is represented by an FUFA with a deterministic leading automaton.

Problem

• probabilistic model checking
• omega-regular languages
• families of deterministic finite automata
• unambiguous finite automata
• succinct representation

Innovation

• probabilistic model checking
• omega-regular languages
• families of unambiguous finite automata
• succinct representation
• LTL translation