D 2023

Reducing Acceptance Marks in Emerson-Lei Automata by QBF Solving

SCHWARZOVÁ, Tereza, Jan STREJČEK and Juraj MAJOR

Basic information

Original name

Reducing Acceptance Marks in Emerson-Lei Automata by QBF Solving

Authors

SCHWARZOVÁ, Tereza (203 Czech Republic, belonging to the institution), Jan STREJČEK (203 Czech Republic, guarantor, belonging to the institution) and Juraj MAJOR (703 Slovakia, belonging to the institution)

Edition

Dagstuhl, Germany, 26th International Conference on Theory and Applications of Satisfiability Testing, SAT 2023, July 4-8, 2023, Alghero, Italy, p. 1-20, 20 pp. 2023

Publisher

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

RIV identification code

RIV/00216224:14330/23:00131935

Organization unit

Faculty of Informatics

ISBN

978-3-95977-286-0

ISSN

DOI

Keywords in English

Emerson-Lei automata; TELA; automata reduction; QBF; telatko

Tags

Tags

International impact, Reviewed
Změněno: 19/3/2024 13:57, prof. RNDr. Jan Strejček, Ph.D.

Abstract

V originále

This paper presents a novel application of QBF solving to automata reduction. We focus on Transition-based Emerson-Lei automata (TELA), which is a popular formalism that generalizes many traditional kinds of automata over infinite words including Büchi, co-Büchi, Rabin, Streett, and parity automata. Transitions in a TELA are labelled with acceptance marks and its accepting formula is a positive Boolean combination of atoms saying that a particular mark has to be visited infinitely or finitely often. Algorithms processing these automata are often very sensitive to the number of acceptance marks. We introduce a new technique for reducing the number of acceptance marks in TELA based on satisfiability of quantified Boolean formulas (QBF). We evaluated our reduction technique on TELA produced by state-of-the-art tools of the libraries Owl and Spot and by the tool ltl3tela. The technique reduced some acceptance marks in automata produced by all the tools. On automata with more than one acceptance mark obtained by translation of LTL formulas from literature with tools Delag and Rabinizer 4, our technique reduced 27.7% and 39.3% of acceptance marks, respectively. The reduction was even higher on automata from random formulas.

Links

MUNI/A/1433/2022, interní kód MU
Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 23
Investor: Masaryk University
101087529, interní kód MU
Name: Cyber-security Excellence Hub in Estonia and South Moravia (CHESS)
Investor: European Union, Cyber-security Excellence Hub in Estonia and South Moravia (CHESS), Widening participation and strengthening the European Research Area