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Global Guidance for Local Generalization in Model Checking
SMT-based model checkers, especially IC3-style ones, are currently the most effective techniques for verification of infinite state systems. They infer global inductive invariants via local reasoning about a single step of the transition relation of a system, while employing SMT-based procedures, su...
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/PMC7363188/ http://dx.doi.org/10.1007/978-3-030-53291-8_7 |
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author | Vediramana Krishnan, Hari Govind Chen, YuTing Shoham, Sharon Gurfinkel, Arie |
author_facet | Vediramana Krishnan, Hari Govind Chen, YuTing Shoham, Sharon Gurfinkel, Arie |
author_sort | Vediramana Krishnan, Hari Govind |
collection | PubMed |
description | SMT-based model checkers, especially IC3-style ones, are currently the most effective techniques for verification of infinite state systems. They infer global inductive invariants via local reasoning about a single step of the transition relation of a system, while employing SMT-based procedures, such as interpolation, to mitigate the limitations of local reasoning and allow for better generalization. Unfortunately, these mitigations intertwine model checking with heuristics of the underlying SMT-solver, negatively affecting stability of model checking. In this paper, we propose to tackle the limitations of locality in a systematic manner. We introduce explicit global guidance into the local reasoning performed by IC3-style algorithms. To this end, we extend the SMT-IC3 paradigm with three novel rules, designed to mitigate fundamental sources of failure that stem from locality. We instantiate these rules for the theory of Linear Integer Arithmetic and implement them on top of Spacer solver in Z3. Our empirical results show that GSpacer, Spacer extended with global guidance, is significantly more effective than both Spacer and sole global reasoning, and, furthermore, is insensitive to interpolation. |
format | Online Article Text |
id | pubmed-7363188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73631882020-07-16 Global Guidance for Local Generalization in Model Checking Vediramana Krishnan, Hari Govind Chen, YuTing Shoham, Sharon Gurfinkel, Arie Computer Aided Verification Article SMT-based model checkers, especially IC3-style ones, are currently the most effective techniques for verification of infinite state systems. They infer global inductive invariants via local reasoning about a single step of the transition relation of a system, while employing SMT-based procedures, such as interpolation, to mitigate the limitations of local reasoning and allow for better generalization. Unfortunately, these mitigations intertwine model checking with heuristics of the underlying SMT-solver, negatively affecting stability of model checking. In this paper, we propose to tackle the limitations of locality in a systematic manner. We introduce explicit global guidance into the local reasoning performed by IC3-style algorithms. To this end, we extend the SMT-IC3 paradigm with three novel rules, designed to mitigate fundamental sources of failure that stem from locality. We instantiate these rules for the theory of Linear Integer Arithmetic and implement them on top of Spacer solver in Z3. Our empirical results show that GSpacer, Spacer extended with global guidance, is significantly more effective than both Spacer and sole global reasoning, and, furthermore, is insensitive to interpolation. 2020-06-16 /pmc/articles/PMC7363188/ http://dx.doi.org/10.1007/978-3-030-53291-8_7 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 Vediramana Krishnan, Hari Govind Chen, YuTing Shoham, Sharon Gurfinkel, Arie Global Guidance for Local Generalization in Model Checking |
title | Global Guidance for Local Generalization in Model Checking |
title_full | Global Guidance for Local Generalization in Model Checking |
title_fullStr | Global Guidance for Local Generalization in Model Checking |
title_full_unstemmed | Global Guidance for Local Generalization in Model Checking |
title_short | Global Guidance for Local Generalization in Model Checking |
title_sort | global guidance for local generalization in model checking |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363188/ http://dx.doi.org/10.1007/978-3-030-53291-8_7 |
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