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      Modelling an Automotive Software-Intensive System with Adaptive Features Using ASMETA

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          Abstract

          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.

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          The vision of autonomic computing

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            Abstract state machines capture parallel algorithms

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              A model-driven process for engineering a toolset for a formal method

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                Author and article information

                Contributors
                alexander.raschke@uni-ulm.de
                dominique.mery@loria.fr
                frank.houdek@daimler.com
                arcaini@nii.ac.jp
                silvia.bonfanti@unibg.it
                angelo.gargantini@unibg.it
                elvinia.riccobene@unimi.it
                patrizia.scandurra@unibg.it
                Journal
                978-3-030-48077-6
                10.1007/978-3-030-48077-6
                Rigorous State-Based Methods
                Rigorous State-Based Methods
                7th International Conference, ABZ 2020, Ulm, Germany, May 27–29, 2020, Proceedings
                978-3-030-48076-9
                978-3-030-48077-6
                22 April 2020
                : 12071
                : 302-317
                Affiliations
                [8 ]GRID grid.6582.9, ISNI 0000 0004 1936 9748, Institute of Software Engineering and Programming Languages, , Ulm University, ; Ulm, Germany
                [9 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, LORIA, Campus Scientifique, , Université de Lorraine, ; Vandoeuvre-les-Nancy, France
                [10 ]GRID grid.410308.e, ISNI 0000 0004 0572 0912, Research and Development, , Mercedes-Benz AG, ; Sindelfingen, Germany
                [11 ]GRID grid.250343.3, ISNI 0000000110185342, National Institute of Informatics, ; Tokyo, Japan
                [12 ]GRID grid.33236.37, ISNI 0000000106929556, Department of Economics and Technology Management, Information Technology and Production, , Università degli Studi di Bergamo, ; Bergamo, Italy
                [13 ]GRID grid.4708.b, ISNI 0000 0004 1757 2822, Dipartimento di Informatica, , Università degli Studi di Milano, ; Milan, Italy
                Author information
                http://orcid.org/0000-0002-6253-4062
                http://orcid.org/0000-0001-9679-4551
                http://orcid.org/0000-0002-4035-0131
                http://orcid.org/0000-0002-1400-1026
                http://orcid.org/0000-0002-9209-3624
                Article
                25
                10.1007/978-3-030-48077-6_25
                7242031
                3918f270-8ed3-42e4-8073-a41815cc1d5b
                © 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.

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