An EM Algorithm for Record Value Statistics Models in Software Reliability Estimation

This paper proposes an EM (expectation-maximization) algorithm for record value statistics (RVS) models in software reliability estimation. The RVS model provides one of the generalized modeling frameworks to unify several of existing software reliability models described as non-homogeneous Poisson processes (NHPPs). The proposed EM algorithm gives a numerically stable procedure to compute the maximum likelihood estimates of RVS models. In particular, we focus on an RVS model based on a mixture of exponential distributions. As an illustrative example, we also derive a concrete EM algorithm for the well-known Musa-Okumoto logarithmic Poisson execution time model by applying our result.

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