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arXiv · 2606.21976

Probabilistic Model Checking via Families of Deterministic and Unambiguous Finite Automata

Christel Baier·Sascha Klüppelholz·Timm Spork
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Abstract

Families of deterministic finite automata (FDFA) have been introduced as a concise automaton model that characterizes $\omega$-regular languages by processing their ultimately periodic words. FDFA are known to enjoy many good properties and can be exponentially more succinct than deterministic $\omega$-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 $\omega$-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 $\omega$-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 $\omega$-regular languages. FUFA can be exponentially more succinct than both FDFA and unambiguous B\"uchi 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.

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Christel Baier, Sascha Klüppelholz, Timm Spork. 2026-06-20. Probabilistic Model Checking via Families of Deterministic and Unambiguous Finite Automata. https://arxiv.org/abs/2606.21976

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