Abstract
We propose a new class of models for software reliability based on known models employing non-homogeneous Poisson processes, e.g., Musa-Okomoto and Goel-Okomoto models. We show that the general idea of model design is in a combined application of imprecise Bayesian inference and the maximum likelihood approach. We show examples where proposed models show better reliability prediction quality compared to the known ones.
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Original Russian Text © L.V. Utkin, S.I. Zatenko, F.P.A. Coolen, 2008, published in Problemy Upravleniya, 2009, No. 6, pp. 52–58.
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Utkin, L.V., Zatenko, S.I. & Coolen, F.P.A. New interval Bayesian models for software reliability based on non-homogeneous Poisson processes. Autom Remote Control 71, 935–944 (2010). https://doi.org/10.1134/S0005117910050218
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DOI: https://doi.org/10.1134/S0005117910050218