Alexandre Duret-Lutz

Simplifying LTL model checking given prior knowledge

Abstract

We consider the problem of the verification of an LTL specification $\varphi$ on a system $S$ given some prior knowledge $K$, an LTL formula that $S$ is known to satisfy. The automata-theoretic approach to LTL model checking is implemented as an emptiness check of the product $S\otimes A_{\lnot\varphi}$ where $A_{\lnot\varphi}$ is an automaton for the negation of the property. We propose new operations that simplify an automaton $A_{\lnot\varphi}$ givengiven some knowledge automaton $A_K$, to produce an automaton $B$ that can be used instead of $A_{\lnot\varphi}$ for more efficient model checking.Our evaluation of these operations on a large benchmark derived from the MCC’22 competition shows that even with simple knowledge, half of the problems can be definitely answered without running an LTL model checker, and the remaining problems can be simplified significantly.

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Translation of semi-extended regular expressions using derivatives

Abstract

We generalize Antimirov’s notion of linear form of a regular expression, to the Semi-Extended Regular Expressions typically used in the Property Specification Language or SystemVerilog Assertions. Doing so requires extending the construction to handle more operators, and dealing with expressions over alphabets $\Sigma=2^{AP}$ of valuations of atomic propositions. Using linear forms to construct automata labeled by Boolean expressions suggests heuristics that we evaluate. Finally, we study a variant of this translation to automata with accepting transitions: this construction is more natural and provides smaller automata.

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The reactive synthesis competition (SYNTCOMP): 2018-2021

Abstract

We report on the last four editions of the reactive synthesis competition (SYNTCOMP 2018-2021). We briefly describe the evaluation scheme and the experimental setup of SYNTCOMP. Then we introduce new benchmark classes that have been added to the SYNTCOMP library and give an overview of the participants of SYNTCOMP. Finally, we present and analyze the results of our experimental evaluations, including a ranking of tools with respect to quantity and quality—that is, the total size in terms of logic and memory elements—of solutions.

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Dissecting ltlsynt

Abstract

ltlsynt is a tool for synthesizing a reactive circuit satisfying a specification expressed as an LTL formula. ltlsynt generally follows a textbook approach: the LTL specification is translated into a parity game whose winning strategy can be seen as a Mealy machine modeling a valid controller. This article details each step of this approach, and presents various refinements integrated over the years. Some of these refinements are unique to ltlsynt: for instance, ltlsynt supports multiple ways to encode a Mealy machine as an AIG circuit, features multiple simplification algorithms for the intermediate Mealy machine, and bypasses the usual game-theoretic approach for some subclasses of LTL formulas in favor of more direct constructions.

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The Mealy-machine reduction functions of Spot

Abstract

We present functions for reducing Mealy machines, initially detailed in our FORTE’22 article. These functions are now integrated into Spot 2.11.2, where they are used as part of the ltlsynt tool for reactive synthesis. Of course, since Spot is a library, these functions can also be used on their own, and we provide Python bindings for easy experiments. The reproducible capsule benchmarks these functions on Mealy machines from various sources, and compare them to the MeMin tool.

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From Spot 2.0 to Spot 2.10: What’s new?

Abstract

Spot is a C++17 library for LTL and $\omega$-automata manipulation, with command-line utilities, and Python bindings. This paper summarizes its evolution over the past six years, since the release of Spot 2.0, which was the first version to support $\omega$-automata with arbitrary acceptance conditions, and the last version presented at a conference. Since then, Spot has been extended with several features such as acceptance transformations, alternating automata, games, LTL synthesis, and more. We also shed some lights on the data-structure used to store automata.

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The reactive synthesis competition (SYNTCOMP): 2018-2021

Abstract

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Effective reductions of Mealy machines

Abstract

We revisit the problem of reducing incompletely specified Mealy machines with reactive synthesis in mind. We propose two techniques: the former is inspired by the tool MeMin and solves the minimization problem, the latter is a novel approach derived from simulation-based reductions but may not guarantee a minimized machine. However, we argue that it offers a good enough compromise between the size of the resulting Mealy machine and performance. The proposed methods are benchmarked against MeMin on a large collection of test cases made of well-known instances as well as new ones.

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Practical applications of the Alternating Cycle Decomposition

Abstract

In 2021, Casares, Colcombet, and Fijalkow introduced the Alternating Cycle Decomposition (ACD) to study properties and transformations of Muller automata. We present the first practical implementation of the ACD in two different tools, Owl and Spot, and adapt it to the framework of Emerson-Lei automata, i.e., $\omega$-automata whose acceptance conditions are defined by Boolean formulas. The ACD provides a transformation of Emerson-Lei automata into parity automata with strong optimality guarantees: the resulting parity automaton is minimal among those automata that can be obtained by duplication of states. Our empirical results show that this transformation is usable in practice. Further, we show how the ACD can generalize many other specialized constructions such as deciding typeness of automata and degeneralization of generalized Büchi automata, providing a framework of practical algorithms for $\omega$-automata.

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Practical “paritizing” of Emerson–Lei automata

Abstract

We introduce a new algorithm that takes a Transition-based Emerson-Lei Automaton (TELA), that is, an $\omega$-automaton whose acceptance condition is an arbitrary Boolean formula on sets of transitions to be seen infinitely or finitely often, and converts it into a Transition-based Parity Automaton (TPA). To reduce the size of the output TPA, the algorithm combines and optimizes two procedures based on a latest appearance record principle, and introduces a partial degeneralization. Our motivation is to use this algorithm to improve our LTL synthesis tool, where producing deterministic parity automata is an intermediate step.

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