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A reward-based performability modelling of a fault-tolerant safety–critical system

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Abstract

Nowadays, various computer system carries out critical functions. The failure of these systems leads to unacceptable loss. Such systems are called Safety–Critical Systems (SCS). The Performance and Reliability of SCS should be high. So, the combined study of performance and reliability (called Performability) is an important issue. The testing of the system is also used to improve its performance. However, some issues might not be addressed in the testing procedure. Formal verification is used for developing secure software. In most of the research work, performability is obtained by operational systems or fail repair systems. Some studies have considered the fail-repair, including fault-tolerant systems. Safety–critical systems generally have fault-tolerant mechanisms to minimize the severity of the failure. This paper studies the safety–critical system's performability using the continuous-time Markov chain (CTMC) with a reward called the Markov reward model (MRM), keeping in mind the fail-repair, fault-tolerant characteristics of the systems. The various parameters of the performability have been analyzed. For mathematical calculation, python language is used. The case study illustrates the proposed approach.

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Authors and Affiliations

  1. Software Quality Assurance Lab, School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Shakeel Ahamad & Ratneshwer Gupta

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  1. Shakeel Ahamad
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  2. Ratneshwer Gupta
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Correspondence to Shakeel Ahamad.

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Ahamad, S., Gupta, R. A reward-based performability modelling of a fault-tolerant safety–critical system. Int J Syst Assur Eng Manag 14, 2218–2234 (2023). https://doi.org/10.1007/s13198-023-02055-3

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  • DOI: https://doi.org/10.1007/s13198-023-02055-3

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