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Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA
In the context of automotive domain, modern control systems are software-intensive and have adaptive features to provide safety and comfort. These software-based features demand software engineering approaches and formal methods that are able to guarantee correct operation, since malfunctions may ca...
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/PMC7242031/ http://dx.doi.org/10.1007/978-3-030-48077-6_25 |
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author | Arcaini, Paolo Bonfanti, Silvia Gargantini, Angelo Riccobene, Elvinia Scandurra, Patrizia |
author_facet | Arcaini, Paolo Bonfanti, Silvia Gargantini, Angelo Riccobene, Elvinia Scandurra, Patrizia |
author_sort | Arcaini, Paolo |
collection | PubMed |
description | In the context of automotive domain, modern control systems are software-intensive and have adaptive features to provide safety and comfort. These software-based features demand software engineering approaches and formal methods that are able to guarantee correct operation, since malfunctions may cause harm/damage. Adaptive Exterior Light and the Speed Control Systems are examples of software-intensive systems that equip modern cars. We have used the Abstract State Machines to model the behaviour of both control systems. Each model has been developed through model refinement, following the incremental way in which functional requirements are given. We used the ASMETA tool-set to support the simulation of the abstract models, their validation against the informal requirements, and the verification of behavioural properties. In this paper, we discuss our modelling, validation and verification strategies, and the results (in terms of features addressed and not) of our activities. In particular, we provide insights on how we addressed the adaptive features (the adaptive high beam headlights and the adaptive cruise control) by explicitly modelling their software control loops according to the MAPE-K (Monitor-Analyse-Plan-Execute over a shared Knowledge) reference control model for self-adaptive systems. |
format | Online Article Text |
id | pubmed-7242031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72420312020-05-22 Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA Arcaini, Paolo Bonfanti, Silvia Gargantini, Angelo Riccobene, Elvinia Scandurra, Patrizia Rigorous State-Based Methods Article In the context of automotive domain, modern control systems are software-intensive and have adaptive features to provide safety and comfort. These software-based features demand software engineering approaches and formal methods that are able to guarantee correct operation, since malfunctions may cause harm/damage. Adaptive Exterior Light and the Speed Control Systems are examples of software-intensive systems that equip modern cars. We have used the Abstract State Machines to model the behaviour of both control systems. Each model has been developed through model refinement, following the incremental way in which functional requirements are given. We used the ASMETA tool-set to support the simulation of the abstract models, their validation against the informal requirements, and the verification of behavioural properties. In this paper, we discuss our modelling, validation and verification strategies, and the results (in terms of features addressed and not) of our activities. In particular, we provide insights on how we addressed the adaptive features (the adaptive high beam headlights and the adaptive cruise control) by explicitly modelling their software control loops according to the MAPE-K (Monitor-Analyse-Plan-Execute over a shared Knowledge) reference control model for self-adaptive systems. 2020-04-22 /pmc/articles/PMC7242031/ http://dx.doi.org/10.1007/978-3-030-48077-6_25 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 Arcaini, Paolo Bonfanti, Silvia Gargantini, Angelo Riccobene, Elvinia Scandurra, Patrizia Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA |
title | Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA |
title_full | Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA |
title_fullStr | Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA |
title_full_unstemmed | Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA |
title_short | Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA |
title_sort | modelling an automotive software-intensive system with adaptive features using asmeta |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242031/ http://dx.doi.org/10.1007/978-3-030-48077-6_25 |
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