Cargando…

Sorting Parity Encodings by Reusing Variables

Parity reasoning is challenging for CDCL solvers: Refuting a formula consisting of two contradictory, differently ordered parity constraints of modest size is hard. Two alternative methods can solve these reordered parity formulas efficiently: binary decision diagrams and Gaussian Elimination (which...

Descripción completa

Detalles Bibliográficos
Autores principales: Chew, Leroy, Heule, Marijn J. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326471/
http://dx.doi.org/10.1007/978-3-030-51825-7_1
_version_ 1783552350976212992
author Chew, Leroy
Heule, Marijn J. H.
author_facet Chew, Leroy
Heule, Marijn J. H.
author_sort Chew, Leroy
collection PubMed
description Parity reasoning is challenging for CDCL solvers: Refuting a formula consisting of two contradictory, differently ordered parity constraints of modest size is hard. Two alternative methods can solve these reordered parity formulas efficiently: binary decision diagrams and Gaussian Elimination (which requires detection of the parity constraints). Yet, implementations of these techniques either lack support of proof logging or introduce many extension variables. The compact, commonly-used encoding of parity constraints uses Tseitin variables. We present a technique for short clausal proofs that exploits these Tseitin variables to reorder the constraints within the DRAT system. The size of our refutations of reordered parity formulas is [Formula: see text].
format Online
Article
Text
id pubmed-7326471
institution National Center for Biotechnology Information
language English
publishDate 2020
record_format MEDLINE/PubMed
spelling pubmed-73264712020-07-01 Sorting Parity Encodings by Reusing Variables Chew, Leroy Heule, Marijn J. H. Theory and Applications of Satisfiability Testing – SAT 2020 Article Parity reasoning is challenging for CDCL solvers: Refuting a formula consisting of two contradictory, differently ordered parity constraints of modest size is hard. Two alternative methods can solve these reordered parity formulas efficiently: binary decision diagrams and Gaussian Elimination (which requires detection of the parity constraints). Yet, implementations of these techniques either lack support of proof logging or introduce many extension variables. The compact, commonly-used encoding of parity constraints uses Tseitin variables. We present a technique for short clausal proofs that exploits these Tseitin variables to reorder the constraints within the DRAT system. The size of our refutations of reordered parity formulas is [Formula: see text]. 2020-06-26 /pmc/articles/PMC7326471/ http://dx.doi.org/10.1007/978-3-030-51825-7_1 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Chew, Leroy
Heule, Marijn J. H.
Sorting Parity Encodings by Reusing Variables
title Sorting Parity Encodings by Reusing Variables
title_full Sorting Parity Encodings by Reusing Variables
title_fullStr Sorting Parity Encodings by Reusing Variables
title_full_unstemmed Sorting Parity Encodings by Reusing Variables
title_short Sorting Parity Encodings by Reusing Variables
title_sort sorting parity encodings by reusing variables
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326471/
http://dx.doi.org/10.1007/978-3-030-51825-7_1
work_keys_str_mv AT chewleroy sortingparityencodingsbyreusingvariables
AT heulemarijnjh sortingparityencodingsbyreusingvariables