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TarTar: A Timed Automata Repair Tool

We present TarTar, an automatic repair analysis tool that, given a timed diagnostic trace (TDT) obtained during the model checking of a timed automaton model, suggests possible syntactic repairs of the analyzed model. The suggested repairs include modified values for clock bounds in location invaria...

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Detalles Bibliográficos
Autores principales: Kölbl, Martin, Leue, Stefan, Wies, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363223/
http://dx.doi.org/10.1007/978-3-030-53288-8_25
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author Kölbl, Martin
Leue, Stefan
Wies, Thomas
author_facet Kölbl, Martin
Leue, Stefan
Wies, Thomas
author_sort Kölbl, Martin
collection PubMed
description We present TarTar, an automatic repair analysis tool that, given a timed diagnostic trace (TDT) obtained during the model checking of a timed automaton model, suggests possible syntactic repairs of the analyzed model. The suggested repairs include modified values for clock bounds in location invariants and transition guards, adding or removing clock resets, etc. The proposed repairs guarantee that the given TDT is no longer feasible in the repaired model, while preserving the overall functional behavior of the system. We give insights into the design and architecture of TarTar, and show that it can successfully repair 69% of the seeded errors in system models taken from a diverse suite of case studies.
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spelling pubmed-73632232020-07-16 TarTar: A Timed Automata Repair Tool Kölbl, Martin Leue, Stefan Wies, Thomas Computer Aided Verification Article We present TarTar, an automatic repair analysis tool that, given a timed diagnostic trace (TDT) obtained during the model checking of a timed automaton model, suggests possible syntactic repairs of the analyzed model. The suggested repairs include modified values for clock bounds in location invariants and transition guards, adding or removing clock resets, etc. The proposed repairs guarantee that the given TDT is no longer feasible in the repaired model, while preserving the overall functional behavior of the system. We give insights into the design and architecture of TarTar, and show that it can successfully repair 69% of the seeded errors in system models taken from a diverse suite of case studies. 2020-06-13 /pmc/articles/PMC7363223/ http://dx.doi.org/10.1007/978-3-030-53288-8_25 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
Kölbl, Martin
Leue, Stefan
Wies, Thomas
TarTar: A Timed Automata Repair Tool
title TarTar: A Timed Automata Repair Tool
title_full TarTar: A Timed Automata Repair Tool
title_fullStr TarTar: A Timed Automata Repair Tool
title_full_unstemmed TarTar: A Timed Automata Repair Tool
title_short TarTar: A Timed Automata Repair Tool
title_sort tartar: a timed automata repair tool
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363223/
http://dx.doi.org/10.1007/978-3-030-53288-8_25
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