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

V. S. Akilandeswari (), R. Poornima () and V. Saavithri ()
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V. S. Akilandeswari: Saranathan College of Engineering
R. Poornima: Nehru Memorial College
V. Saavithri: Nehru Memorial College

OPSEARCH, 2017, vol. 54, issue 2, No 2, 233-259

Abstract: 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.

Keywords: Statistical Process Control (SPC); Non-Homogeneous Poisson Process (NHPP); Goel–Okumoto; Weibull; Pareto Type III; Kumaraswamy Modified Inverse Weibull (KMIW); Lehmann-Type Laplace distribution Type I (LLD-Type I); Profile Likelihood; Akaike Information Criterion (AIC); Bayesian Information Criterion (BIC) (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s12597-016-0281-6

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