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Lehmann-Type Laplace distribution-Type I software reliability growth model

Author

Listed:
  • V. S. Akilandeswari

    (Saranathan College of Engineering)

  • R. Poornima

    (Nehru Memorial College)

  • V. Saavithri

    (Nehru Memorial College)

Abstract

In this paper, Lehmann-Type Laplace Type I reliability growth model is proposed for early detection of software failure based on time between failure observations. Cumulative time between failures of the software data is assumed to follow Lehmann-Type Laplace distribution-Type I (LLD-Type I). The parameters are estimated using Profile Likelihood Method. In terms of AIC and BIC, this distribution is found to be a better fit for the software failure data than Goel–Okumoto, Weibull, Pareto Type III and Kumaraswamy Modified Inverse Weibull distributions which are commonly used in reliability analysis. A LLD-Type I control mechanism is used to detect the failure points of a software data.

Suggested Citation

  • V. S. Akilandeswari & R. Poornima & V. Saavithri, 2017. "Lehmann-Type Laplace distribution-Type I software reliability growth model," OPSEARCH, Springer;Operational Research Society of India, vol. 54(2), pages 233-259, June.
    • Handle: RePEc:spr:opsear:v:54:y:2017:i:2:d:10.1007_s12597-016-0281-6
    DOI: 10.1007/s12597-016-0281-6
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    References listed on IDEAS

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    1. Alexander, Carol & Cordeiro, Gauss M. & Ortega, Edwin M.M. & Sarabia, José María, 2012. "Generalized beta-generated distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1880-1897.
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