Word Equations in Synergy with Regular Constraints

Several new algorithms for deciding emptiness of Boolean combinations of regular languages and of languages of alternating automata have been proposed recently, especially in the context of analysing regular expressions and in string constraint solving. The new algorithms demonstrated a significant potential, but they have never been systematically compared, neither among each other nor with the state-of-the art implementations of existing (non)deterministic automata-based methods. In this paper, we provide such comparison as well as an overview of the existing algorithms and their implementations. We collect a diverse benchmark mostly originating in or related to practical problems from string constraint solving, analysing LTL properties, and regular model checking, and evaluate collected implementations on it. The results reveal the best tools and hint on what the best algorithms and implementation techniques are. Roughly, although some advanced algorithms are fast, such as antichain algorithms and reductions to IC3/PDR, they are not as overwhelmingly dominant as sometimes presented and there is no clear winner. The simplest NFA-based technology may sometimes be a better choice, depending on the problem source and the implementation style. We believe that our findings are relevant for development of automata techniques as well as for related fields such as string constraint solving.

Reasoning About Regular Properties: A Comparative Study

Fiedor,

Holík,

Hruška

et al. 2023

Z3-Noodler: An Automata-based String Solver

Chen,

Chocholatý,

Havlena

et al. 2024

Z3-Noodler is a fork of Z3 that replaces its string theory solver with a custom solver implementing the recently introduced stabilization-based algorithm for solving word equations with regular constraints. An extensive experimental evaluation shows that Z3-Noodler is a fully-fledged solver that can compete with state-of-the-art solvers, surpassing them by far on many benchmarks. Moreover, it is often complementary to other solvers, making it a suitable choice as a candidate to a solver portfolio.

Mata: A Fast and Simple Finite Automata Library

Chocholatý,

Fiedor,

Havlena

et al. 2024

Mata is a well-engineered automata library written in C++ that offers a unique combination of speed and simplicity. It is meant to serve in applications such as string constraint solving and reasoning about regular expressions, and as a reference implementation of automata algorithms. Besides basic algorithms for (non)deterministic automata, it implements a fast simulation reduction and antichain-based language inclusion checking. The simplicity allows a straightforward access to the low-level structures, making it relatively easy to extend and modify. Besides the C++ API, the library also implements a Python binding.The library comes with a large benchmark of automata problems collected from relevant applications such as string constraint solving, regular model checking, and reasoning about regular expressions. We show that Mata is on this benchmark significantly faster than all libraries from a wide range of automata libraries we collected. Its usefulness in string constraint solving is demonstrated by the string solver Z3-Noodler, which is based on Mata and outperforms the state of the art in string constraint solving on many standard benchmarks.