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Mining definitions in Kissat with Kittens

Bounded variable elimination is one of the most important preprocessing techniques in SAT solving. It benefits from discovering functional dependencies in the form of definitions encoded in the CNF. While the common approach pioneered in SatELite relies on syntactic pattern matching, our new approac...

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Detalles Bibliográficos
Autores principales: Fleury, Mathias, Biere, Armin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564679/
https://www.ncbi.nlm.nih.gov/pubmed/37829794
http://dx.doi.org/10.1007/s10703-023-00421-2
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author Fleury, Mathias
Biere, Armin
author_facet Fleury, Mathias
Biere, Armin
author_sort Fleury, Mathias
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description Bounded variable elimination is one of the most important preprocessing techniques in SAT solving. It benefits from discovering functional dependencies in the form of definitions encoded in the CNF. While the common approach pioneered in SatELite relies on syntactic pattern matching, our new approach uses cores produced by an embedded SAT solver, Kitten. In contrast to a similar semantic technique implemented in Lingeling based on BDD algorithms to generate irredundant CNFs, our new approach is able to generate DRAT proofs. We further discuss design choices for our embedded SAT solver Kitten. Experiments with Kissat show the effectiveness of this approach.
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spelling pubmed-105646792023-10-12 Mining definitions in Kissat with Kittens Fleury, Mathias Biere, Armin Form Methods Syst Des Article Bounded variable elimination is one of the most important preprocessing techniques in SAT solving. It benefits from discovering functional dependencies in the form of definitions encoded in the CNF. While the common approach pioneered in SatELite relies on syntactic pattern matching, our new approach uses cores produced by an embedded SAT solver, Kitten. In contrast to a similar semantic technique implemented in Lingeling based on BDD algorithms to generate irredundant CNFs, our new approach is able to generate DRAT proofs. We further discuss design choices for our embedded SAT solver Kitten. Experiments with Kissat show the effectiveness of this approach. Springer US 2023-04-24 2022 /pmc/articles/PMC10564679/ /pubmed/37829794 http://dx.doi.org/10.1007/s10703-023-00421-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Fleury, Mathias
Biere, Armin
Mining definitions in Kissat with Kittens
title Mining definitions in Kissat with Kittens
title_full Mining definitions in Kissat with Kittens
title_fullStr Mining definitions in Kissat with Kittens
title_full_unstemmed Mining definitions in Kissat with Kittens
title_short Mining definitions in Kissat with Kittens
title_sort mining definitions in kissat with kittens
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564679/
https://www.ncbi.nlm.nih.gov/pubmed/37829794
http://dx.doi.org/10.1007/s10703-023-00421-2
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