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Nonlinear Craig Interpolant Generation
Craig interpolant generation for non-linear theory and its combination with other theories are still in infancy, although interpolation-based techniques have become popular in the verification of programs and hybrid systems where non-linear expressions are very common. In this paper, we first prove...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363235/ http://dx.doi.org/10.1007/978-3-030-53288-8_20 |
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author | Gan, Ting Xia, Bican Xue, Bai Zhan, Naijun Dai, Liyun |
author_facet | Gan, Ting Xia, Bican Xue, Bai Zhan, Naijun Dai, Liyun |
author_sort | Gan, Ting |
collection | PubMed |
description | Craig interpolant generation for non-linear theory and its combination with other theories are still in infancy, although interpolation-based techniques have become popular in the verification of programs and hybrid systems where non-linear expressions are very common. In this paper, we first prove that a polynomial interpolant of the form [Formula: see text] exists for two mutually contradictory polynomial formulas [Formula: see text] and [Formula: see text], with the form [Formula: see text], where [Formula: see text] are polynomials in [Formula: see text] or [Formula: see text], and the quadratic module generated by [Formula: see text] is Archimedean. Then, we show that synthesizing such interpolant can be reduced to solving a semi-definite programming problem ([Formula: see text]). In addition, we propose a verification approach to assure the validity of the synthesized interpolant and consequently avoid the unsoundness caused by numerical error in [Formula: see text] solving. Besides, we discuss how to generalize our approach to general semi-algebraic formulas. Finally, as an application, we demonstrate how to apply our approach to invariant generation in program verification. |
format | Online Article Text |
id | pubmed-7363235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73632352020-07-16 Nonlinear Craig Interpolant Generation Gan, Ting Xia, Bican Xue, Bai Zhan, Naijun Dai, Liyun Computer Aided Verification Article Craig interpolant generation for non-linear theory and its combination with other theories are still in infancy, although interpolation-based techniques have become popular in the verification of programs and hybrid systems where non-linear expressions are very common. In this paper, we first prove that a polynomial interpolant of the form [Formula: see text] exists for two mutually contradictory polynomial formulas [Formula: see text] and [Formula: see text], with the form [Formula: see text], where [Formula: see text] are polynomials in [Formula: see text] or [Formula: see text], and the quadratic module generated by [Formula: see text] is Archimedean. Then, we show that synthesizing such interpolant can be reduced to solving a semi-definite programming problem ([Formula: see text]). In addition, we propose a verification approach to assure the validity of the synthesized interpolant and consequently avoid the unsoundness caused by numerical error in [Formula: see text] solving. Besides, we discuss how to generalize our approach to general semi-algebraic formulas. Finally, as an application, we demonstrate how to apply our approach to invariant generation in program verification. 2020-06-13 /pmc/articles/PMC7363235/ http://dx.doi.org/10.1007/978-3-030-53288-8_20 Text en © The Author(s) 2020 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), 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 license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license 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. |
spellingShingle | Article Gan, Ting Xia, Bican Xue, Bai Zhan, Naijun Dai, Liyun Nonlinear Craig Interpolant Generation |
title | Nonlinear Craig Interpolant Generation |
title_full | Nonlinear Craig Interpolant Generation |
title_fullStr | Nonlinear Craig Interpolant Generation |
title_full_unstemmed | Nonlinear Craig Interpolant Generation |
title_short | Nonlinear Craig Interpolant Generation |
title_sort | nonlinear craig interpolant generation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363235/ http://dx.doi.org/10.1007/978-3-030-53288-8_20 |
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