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Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases

We address the satisfiability of systems of polynomial equations over bit-vectors. Instead of conventional bit-blasting, we exploit word-level inference to translate these systems into non-linear pseudo-boolean constraints. We derive the pseudo-booleans by simulating bit assignments through the addi...

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Detalles Bibliográficos
Autores principales: Seed, Thomas, King, Andy, Evans, Neil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326557/
http://dx.doi.org/10.1007/978-3-030-51825-7_26
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author Seed, Thomas
King, Andy
Evans, Neil
author_facet Seed, Thomas
King, Andy
Evans, Neil
author_sort Seed, Thomas
collection PubMed
description We address the satisfiability of systems of polynomial equations over bit-vectors. Instead of conventional bit-blasting, we exploit word-level inference to translate these systems into non-linear pseudo-boolean constraints. We derive the pseudo-booleans by simulating bit assignments through the addition of (linear) polynomials and applying a strong form of propagation by computing Gröbner bases. By handling bit assignments symbolically, the number of Gröbner basis calculations, along with the number of assignments, is reduced. The final Gröbner basis yields expressions for the bit-vectors in terms of the symbolic bits, together with non-linear pseudo-boolean constraints on the symbolic variables, modulo a power of two. The pseudo-booleans can be solved by translation into classical linear pseudo-boolean constraints (without a modulo) or by encoding them as propositional formulae, for which a novel translation process is described.
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spelling pubmed-73265572020-07-01 Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases Seed, Thomas King, Andy Evans, Neil Theory and Applications of Satisfiability Testing – SAT 2020 Article We address the satisfiability of systems of polynomial equations over bit-vectors. Instead of conventional bit-blasting, we exploit word-level inference to translate these systems into non-linear pseudo-boolean constraints. We derive the pseudo-booleans by simulating bit assignments through the addition of (linear) polynomials and applying a strong form of propagation by computing Gröbner bases. By handling bit assignments symbolically, the number of Gröbner basis calculations, along with the number of assignments, is reduced. The final Gröbner basis yields expressions for the bit-vectors in terms of the symbolic bits, together with non-linear pseudo-boolean constraints on the symbolic variables, modulo a power of two. The pseudo-booleans can be solved by translation into classical linear pseudo-boolean constraints (without a modulo) or by encoding them as propositional formulae, for which a novel translation process is described. 2020-06-26 /pmc/articles/PMC7326557/ http://dx.doi.org/10.1007/978-3-030-51825-7_26 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
Seed, Thomas
King, Andy
Evans, Neil
Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases
title Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases
title_full Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases
title_fullStr Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases
title_full_unstemmed Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases
title_short Reducing Bit-Vector Polynomials to SAT Using Gröbner Bases
title_sort reducing bit-vector polynomials to sat using gröbner bases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326557/
http://dx.doi.org/10.1007/978-3-030-51825-7_26
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