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Trivariate Bernoulli distribution with application to software fault tolerance

Author

Listed:
  • Lance Fiondella

    (University of Massachusetts)

  • Panlop Zeephongsekul

    (RMIT University)

Abstract

The widespread reliance on software for mission and life critical applications makes the reliability of these systems essential. Techniques such as fault tolerance have been proposed to achieve the highest levels of software reliability. However, the fault tolerance paradigm suffers from the risk of correlated failures, where a majority of the software versions fail on the same input leading to system failure. This paper derives a trivariate Bernoulli distribution to quantify the negative impact of correlated failures on the reliability of fault tolerant software composed of highly reliable versions. An experiment based on early empirical research demonstrates the capacity of the distribution to conduct reliability assessment for many combinations of the version reliabilities and correlations. The results indicate that correlated failures detract from system reliability, but that this reliability is often higher than a system composed of the single most reliable version.

Suggested Citation

  • Lance Fiondella & Panlop Zeephongsekul, 2016. "Trivariate Bernoulli distribution with application to software fault tolerance," Annals of Operations Research, Springer, vol. 244(1), pages 241-255, September.
    • Handle: RePEc:spr:annopr:v:244:y:2016:i:1:d:10.1007_s10479-015-1798-4
    DOI: 10.1007/s10479-015-1798-4
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    Cited by:

    1. Alessandro Barbiero, 2022. "Properties and estimation of a bivariate geometric model with locally constant failure rates," Annals of Operations Research, Springer, vol. 312(1), pages 3-22, May.
    2. Jafary, Bentolhoda & Mele, Andrew & Fiondella, Lance, 2020. "Component-based system reliability subject to positive and negative correlation," Reliability Engineering and System Safety, Elsevier, vol. 202(C).

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