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An Integrated Approach to Support the Process-Based Certification of Variant-Intensive Systems

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Model-Based Safety and Assessment (IMBSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12297))

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Abstract

Component-based approaches and software product lines have been adopted by industry to manage the diversity of configurations on safety-critical software. Safety certification demands compliance with standards. ISO 26262 standard uses the concept of Automotive Safety Integrity Level (ASIL) to allocate safety requirements to components of a system under design. Compliance with standards is demonstrated through achieving those ASILs which can be very expensive when requirements are high. While achieving safety certification of variant-intensive components without being unnecessarily stringent or expensive is desirable for economy, it poses challenges to safety engineering. In this paper, we propose an approach to manage the diversity of safety goals and supporting safety certification of software components. Our approach is built upon the integration among ASIL decomposition, software process modeling, and variability management techniques. The approach supports cost-effective safety certification and the efficient tailoring of process models to components according to their ASILs. We evaluated our approach in the automotive domain. The approach is feasible in supporting the management of the diversity of safety goals, and cost-effective safety certification of software components.

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Notes

  1. 1.

    https://www.eclipse.org/epf/.

  2. 2.

    https://www.amass-ecsel.eu/content/about.

  3. 3.

    https://github.com/bressan3/HBS-HipHops-Results/tree/master/pseudocode.

  4. 4.

    https://github.com/bressan3/HBS-PL.

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Correspondence to Lucas Bressan .

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Bressan, L., de Oliveira, A.L., Campos, F., Papadopoulos, Y., Parker, D. (2020). An Integrated Approach to Support the Process-Based Certification of Variant-Intensive Systems. In: Zeller, M., Höfig, K. (eds) Model-Based Safety and Assessment. IMBSA 2020. Lecture Notes in Computer Science(), vol 12297. Springer, Cham. https://doi.org/10.1007/978-3-030-58920-2_12

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  • DOI: https://doi.org/10.1007/978-3-030-58920-2_12

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