Tunable Online MUS/MSS Enumeration

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Authors

BENDÍK Jaroslav BENEŠ Nikola ČERNÁ Ivana BARNAT Jiří

Year of publication 2016
Type Article in Proceedings
Conference Foundations of Software Technology and Theoretical Computer Science - 36th International Conference, FSTTCS 2016
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.4230/LIPIcs.FSTTCS.2016.50
Field Informatics
Keywords Minimal unsatisfiable subsets; Maximal satisfiable subsets; Unsatisfiability analysis; Infeasibility analysis
Description In various areas of computer science, the problem of dealing with a set of constraints arises. If the set of constraints is unsatisfiable, one may ask for a minimal description of the reason for this unsatisifiability. Minimal unsatisfiable subsets (MUSes) and maximal satisfiable subsets (MSSes) are two kinds of such minimal descriptions. The goal of this work is the enumeration of MUSes and MSSes for a given constraint system. As such full enumeration may be intractable in general, we focus on building an online algorithm, which produces MUSes/MSSes in an on-the-fly manner as soon as they are discovered. The problem has been studied before even in its online version. However, our algorithm uses a novel approach that is able to outperform the current state-of-the-art algorithms for online MUS/MSS enumeration. Moreover, the performance of our algorithm can be adjusted using tunable parameters. We evaluate the algorithm on a set of benchmarks.
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