BENDÍK, Jaroslav and Ivana ČERNÁ. Evaluation of Domain Agnostic Approaches for Enumeration of Minimal Unsatisfiable Subsets. Online. In Gilles Barthe and Geoff Sutcliffe and Margus Veanes. LPAR-22, 22nd International Conference on Logic for Programming, Artificial Intelligence and Reasoning. Awassa, Etiopie: EPiC Series in Computing, 2018, p. 131-142. ISSN 2398-7340. Available from: https://dx.doi.org/10.29007/sxzb.
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Basic information
Original name Evaluation of Domain Agnostic Approaches for Enumeration of Minimal Unsatisfiable Subsets
Authors BENDÍK, Jaroslav (203 Czech Republic, guarantor, belonging to the institution) and Ivana ČERNÁ (203 Czech Republic, belonging to the institution).
Edition Awassa, Etiopie, LPAR-22, 22nd International Conference on Logic for Programming, Artificial Intelligence and Reasoning, p. 131-142, 12 pp. 2018.
Publisher EPiC Series in Computing
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
RIV identification code RIV/00216224:14330/18:00104038
Organization unit Faculty of Informatics
ISSN 2398-7340
Doi http://dx.doi.org/10.29007/sxzb
Keywords in English minimal unsatisfiable subsets;mus enumeration;infeasibility analysis;unsatisfiability analysis
Tags core_A, firank_A
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 31/5/2022 14:21.
Abstract
In many different applications we are given a set of constraints with the goal to decide whether the set is satisfiable. If the set is determined to be unsatisfiable, one might be interested in analysing this unsatisfiability. Identification of minimal unsatisfiable subsets (MUSes) is a kind of such analysis. The more MUSes are identified, the better insight into the unsatisfiability is obtained. However, the full enumeration of all MUSes is often intractable. Therefore, algorithms that identify MUSes in an online fashion, i.e., one by one, are needed. Moreover, since MUSes find applications in various constraint domains, and new applications still arise, there is a desire for domain agnostic MUS enumeration approaches. In this paper, we present an experimental evaluation of four state-of-the-art domain agnostic MUS enumeration algorithms: MARCO, TOME, ReMUS, and DAA. The evaluation is conducted in the SAT, SMT, and LTL constraint domains. The results evidence that there is no silver-bullet algorithm that would beat all the others in all the domains.
Links
MUNI/A/0854/2017, interní kód MUName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VII.
Investor: Masaryk University, Category A
MUNI/A/1038/2017, interní kód MUName: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 18
Investor: Masaryk University, Category A
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