BENDÍK, Jaroslav and Ivana ČERNÁ. MUST: Minimal Unsatisfiable Subsets Enumeration Tool. Online. In Armin Biere and David Parker. Tools and Algorithms for the Construction and Analysis of Systems. Neuveden: Springer International Publishing, 2020. p. 135-152. ISBN 978-3-030-45189-9. Available from: https://dx.doi.org/10.1007/978-3-030-45190-5_8. [citováno 2024-04-24]
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Basic information
Original name MUST: Minimal Unsatisfiable Subsets Enumeration Tool
Authors BENDÍK, Jaroslav (203 Czech Republic, guarantor, belonging to the institution) and Ivana ČERNÁ (203 Czech Republic, belonging to the institution)
Edition Neuveden, Tools and Algorithms for the Construction and Analysis of Systems, p. 135-152, 18 pp. 2020.
Publisher Springer International Publishing
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10200 1.2 Computer and information sciences
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/20:00115396
Organization unit Faculty of Informatics
ISBN 978-3-030-45189-9
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-030-45190-5_8
Keywords in English Minimal unsatisfiable subsets;Unsatisfiability analysis;Infeasibility analysis;MUS;Diagnosis
Tags core_A, firank_A
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 10/5/2021 05:40.
Abstract
In many areas of computer science, we are given an unsatisfiable set of constraints with the goal to provide an insight into the unsatisfiability. One of common approaches is to identify minimal unsatisfiable subsets (MUSes) of the constraint set. The more MUSes are identified, the better insight is obtained. However, since there can be up to exponentially many MUSes, their complete enumeration might be intractable. Therefore, we focus on algorithms that enumerate MUSes online, i.e. one by one, and thus can find at least some MUSes even in the intractable cases. Since MUSes find applications in different constraint domains and new applications still arise, there have been proposed several domain agnostic algorithms. Such algorithms can be applied in any constraint domain and thus theoretically serve as ready-to-use solutions for all the emerging applications. However, there are almost no domain agnostic tools, i.e. tools that both implement domain agnostic algorithms and can be easily extended to support any constraint domain. In this work, we close this gap by introducing a domain agnostic tool called MUST. Our tool outperforms other existing domain agnostic tools and moreover, it is even competitive to fully domain specific solutions.
Links
EF16_019/0000822, research and development projectName: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur
MUNI/A/1050/2019, interní kód MUName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace IX (Acronym: SV-FI MAV IX)
Investor: Masaryk University, Category A
MUNI/A/1076/2019, interní kód MUName: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 20 (Acronym: SKOMU)
Investor: Masaryk University, Category A
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