A Markov modulated Poisson model for software reliability |
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| Authors: | Joshua Landon,Sü leyman Ö zekici,Refik Soyer |
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| Affiliation: | 1. The George Washington University, Department of Statistics, Washington, DC 20052, USA;2. Koç University, Department of Industrial Engineering, 34450 ?stanbul, Turkey;3. The George Washington University, Department of Decision Sciences, Washington, DC 20052, USA |
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| Abstract: | In this paper, we consider a latent Markov process governing the intensity rate of a Poisson process model for software failures. The latent process enables us to infer performance of the debugging operations over time and allows us to deal with the imperfect debugging scenario. We develop the Bayesian inference for the model and also introduce a method to infer the unknown dimension of the Markov process. We illustrate the implementation of our model and the Bayesian approach by using actual software failure data. |
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| Keywords: | Software reliability Hidden Markov model Bayesian inference |
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