Multifaceted Automated Analyses for Variability-Intensive Embedded Systems

Abstract : Embedded systems, like those found in the automotive domain, must comply with stringent functional and non-functional requirements. To fulfil these requirements, engineers are confronted with a plethora of design alternatives both at the software and hardware level, out of which they must select the optimal solution wrt. possibly-antagonistic quality attributes (e.g. cost of manufacturing vs. speed of execution). We propose a model-driven framework to assist engineers in this choice. It captures high-level specifications of the system in the form of variable dataflows and configurable hardware platforms. A mapping algorithm then derives the design space, i.e. the set of compatible pairs of application and platform variants, and a variability-aware executable model, which encodes the functional and non-functional behaviour of all viable system variants. Novel verification algorithms then pinpoint the optimal system variants efficiently. The benefits of our approach are evaluated through a real-world case study from the automotive industry.
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Contributor : Sébastien Mosser <>
Submitted on : Friday, March 8, 2019 - 12:43:21 AM
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Sami Lazreg, Maxime Cordy, Philippe Collet, Patrick Heymans, Sébastien Mosser. Multifaceted Automated Analyses for Variability-Intensive Embedded Systems. 41st ACM/IEEE International Conference on Software Engineering, May 2019, Montréal, Canada. ⟨hal-02061251⟩

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