A Markov modulated Poisson model for software reliability

作者：Landon Joshua; Ozekici Suleyman; Soyer Refik^*

来源：European Journal of Operational Research, 2013, 229(2): 404-410.

DOI：10.1016/j.ejor.2013.03.014

• Software reliability
• Hidden Markov model
• Bayesian inference

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.

• 出版日期2013-9-1