License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.SAT.2023.15
URN: urn:nbn:de:0030-drops-184775
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18477/
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Masina, Gabriele ; Spallitta, Giuseppe ; Sebastiani, Roberto

On CNF Conversion for Disjoint SAT Enumeration

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LIPIcs-SAT-2023-15.pdf (2 MB)


Abstract

Modern SAT solvers are designed to handle problems expressed in Conjunctive Normal Form (CNF) so that non-CNF problems must be CNF-ized upfront, typically by using variants of either Tseitin or Plaisted and Greenbaum transformations. When passing from solving to enumeration, however, the capability of producing partial satisfying assignments that are as small as possible becomes crucial, which raises the question of whether such CNF encodings are also effective for enumeration.
In this paper, we investigate both theoretically and empirically the effectiveness of CNF conversions for disjoint SAT enumeration. On the negative side, we show that: (i) Tseitin transformation prevents the solver from producing short partial assignments, thus seriously affecting the effectiveness of enumeration; (ii) Plaisted and Greenbaum transformation overcomes this problem only in part. On the positive side, we show that combining Plaisted and Greenbaum transformation with NNF preprocessing upfront - which is typically not used in solving - can fully overcome the problem and can drastically reduce both the number of partial assignments and the execution time.

BibTeX - Entry

@InProceedings{masina_et_al:LIPIcs.SAT.2023.15,
  author =	{Masina, Gabriele and Spallitta, Giuseppe and Sebastiani, Roberto},
  title =	{{On CNF Conversion for Disjoint SAT Enumeration}},
  booktitle =	{26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023)},
  pages =	{15:1--15:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-286-0},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{271},
  editor =	{Mahajan, Meena and Slivovsky, Friedrich},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/18477},
  URN =		{urn:nbn:de:0030-drops-184775},
  doi =		{10.4230/LIPIcs.SAT.2023.15},
  annote =	{Keywords: CNF conversion, AllSAT, AllSMT}
}

Keywords: CNF conversion, AllSAT, AllSMT
Collection: 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023)
Issue Date: 2023
Date of publication: 09.08.2023
Supplementary Material: Software (Source Code): https://github.com/masinag/allsat-cnf archived at: https://archive.softwareheritage.org/swh:1:dir:9fe50303a2947f6392f1601ec3c326a9582fdfb5


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