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Model-based design of resilient systems using quantitative risk assessment

  • S.I. : VECoS 2021
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Abstract

Fault detection, isolation and recovery subsystems are accepted to make safety-critical systems resilient against faults and failures. Yet, these subsystems should be devised only for those faults that violate the system’s requirements, while providing a correct approach such that requirements are met again. Consequently, the obtained system is minimal, although complete, and robust both with respect to safety and performance requirements. In this paper, we propose a systematic and automated approach based on formal methods that includes (1) the evaluation of the relevance of faults based on quantitative risk assessment, and (2) the validation of system robustness by statistical model checking. We apply this approach on an excerpt of a real-life autonomous robotics case study, and we report on the implementation and results obtained with the \(\mathcal {S}\text {BIP}\) framework.

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Notes

  1. BIP stands for Behavior–Interaction–Priority.

  2. See  [28] for the formal definition of the stochastic real-time BIP.

  3. The suffixes out in and return used in Fig. 5 are modeling the directionality of the requests. Out models that the component sends the request. In models that the component receives the request. Return models that the action associated with the request has finished executing.

  4. Notice that the values for P, D, \(\textit{MIAT}\), and size are part of the system specification.

  5. The system architecture and specification, \(\textsf{Watchdog}\) included, have been provided in the frame of this case study such that the used resources (e.g., number of components and threads) are minimal.

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Acknowledgements

This work has been supported by the EU’s H2020 research and innovation programme under grant agreement #730080 (ESROCOS) and #700665 (CITADEL).

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Authors and Affiliations

  1. Huawei Technologies France, Grenoble, France

    Braham Lotfi Mediouni & Ayoub Nouri

  2. GMV Aerospace and Defence, Madrid, Spain

    Iulia Dragomir

  3. Univ. Grenoble Alpes, CNRS, Grenoble INP, VERIMAG, Grenoble, 38000, France

    Saddek Bensalem

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  1. Braham Lotfi Mediouni
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  2. Iulia Dragomir
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  4. Saddek Bensalem
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Correspondence to Braham Lotfi Mediouni.

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The model sources

The model sources used in this manuscript are available at https://drive.google.com/file/d/1oN90ZraClQxAH5hHE2tl7t2IMsZVzo7L/view?usp=drivesdk. The SMC-BIP tool can be downloaded from https://www-verimag.imag.fr/BIP-SMC-A-Statistical-Model-Checking.html.

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Mediouni, B.L., Dragomir, I., Nouri, A. et al. Model-based design of resilient systems using quantitative risk assessment. Innovations Syst Softw Eng 20, 3–16 (2024). https://doi.org/10.1007/s11334-023-00527-0

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