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Bounded Model Checking for Hyperproperties

This paper introduces a bounded model checking (BMC) algorithm for hyperproperties expressed in HyperLTL, which — to the best of our knowledge — is the first such algorithm. Just as the classic BMC technique for LTL primarily aims at finding bugs, our approach also targets identifying counterexample...

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Detalles Bibliográficos
Autores principales: Hsu, Tzu-Han, Sánchez, César, Bonakdarpour, Borzoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7979203/
http://dx.doi.org/10.1007/978-3-030-72016-2_6
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author Hsu, Tzu-Han
Sánchez, César
Bonakdarpour, Borzoo
author_facet Hsu, Tzu-Han
Sánchez, César
Bonakdarpour, Borzoo
author_sort Hsu, Tzu-Han
collection PubMed
description This paper introduces a bounded model checking (BMC) algorithm for hyperproperties expressed in HyperLTL, which — to the best of our knowledge — is the first such algorithm. Just as the classic BMC technique for LTL primarily aims at finding bugs, our approach also targets identifying counterexamples. BMC for LTL is reduced to SAT solving, because LTL describes a property via inspecting individual traces. Our BMC approach naturally reduces to QBF solving, as HyperLTL allows explicit and simultaneous quantification over multiple traces. We report on successful and efficient model checking, implemented in our tool called HyperQube, of a rich set of experiments on a variety of case studies, including security, concurrent data structures, path planning for robots, and mutation testing.
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spelling pubmed-79792032021-03-23 Bounded Model Checking for Hyperproperties Hsu, Tzu-Han Sánchez, César Bonakdarpour, Borzoo Tools and Algorithms for the Construction and Analysis of Systems Article This paper introduces a bounded model checking (BMC) algorithm for hyperproperties expressed in HyperLTL, which — to the best of our knowledge — is the first such algorithm. Just as the classic BMC technique for LTL primarily aims at finding bugs, our approach also targets identifying counterexamples. BMC for LTL is reduced to SAT solving, because LTL describes a property via inspecting individual traces. Our BMC approach naturally reduces to QBF solving, as HyperLTL allows explicit and simultaneous quantification over multiple traces. We report on successful and efficient model checking, implemented in our tool called HyperQube, of a rich set of experiments on a variety of case studies, including security, concurrent data structures, path planning for robots, and mutation testing. 2021-03-01 /pmc/articles/PMC7979203/ http://dx.doi.org/10.1007/978-3-030-72016-2_6 Text en © The Author(s) 2021 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
Hsu, Tzu-Han
Sánchez, César
Bonakdarpour, Borzoo
Bounded Model Checking for Hyperproperties
title Bounded Model Checking for Hyperproperties
title_full Bounded Model Checking for Hyperproperties
title_fullStr Bounded Model Checking for Hyperproperties
title_full_unstemmed Bounded Model Checking for Hyperproperties
title_short Bounded Model Checking for Hyperproperties
title_sort bounded model checking for hyperproperties
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7979203/
http://dx.doi.org/10.1007/978-3-030-72016-2_6
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