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FMUS2: An efficient algorithm to compute minimal unsatisfiable subsets

  • Shaofan Liu
  • , Jie Luo*
  • *此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In the past few years, much attention has been given to the problem of finding Minimal Unsatisfiable Subsets (MUSes), not only for its theoretical importance but also for its wide range of practical applications, including software testing, hardware verification and knowledge-based validation. In this paper, we propose an algorithm for extracting all MUSes for formulas in the field of propositional logic and the function-free and equality-free fragment of first-order logic. This algorithm extends earlier work, but some changes have been made and a number of optimization strategies have been proposed to improve its efficiency. Experimental results show that our algorithm performs well on many industrial and generated instances, and the strategies adopted can indeed improve the efficiency of our algorithm.

源语言英语
主期刊名Artificial Intelligence and Symbolic Computation - 13th International Conference, AISC 2018, Proceedings
编辑Dongming Wang, Jacques Fleuriot, Jacques Calmet
出版商Springer Verlag
104-118
页数15
ISBN(印刷版)9783319999562
DOI
出版状态已出版 - 2018
活动13th International Conference on Artificial Intelligence and Symbolic Computation, AISC 2018 - Suzhou, 中国
期限: 16 9月 201819 9月 2018

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11110 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议13th International Conference on Artificial Intelligence and Symbolic Computation, AISC 2018
国家/地区中国
Suzhou
时期16/09/1819/09/18

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