Failure correlation in software reliability models

Perhaps the most stringent restriction that is present in most software reliability models is the assumption of independence among successive software failures. Our research was motivated by the fact that although there are practical situations in which this assumption could be easily violated, much of the published literature on software reliability modeling does not seriously address this issue. In this paper we present a software reliability modeling framework based on Markov renewal processes which naturally introduces dependence among successive software runs. The presented approach enables the phenomena of failure clustering to be precisely characterized and its effects on software reliability to be analyzed. Furthermore, it also provides bases for a more flexible and consistent model formulation and solution. The Markov renewal model presented in this paper can be related to the existing software reliability growth models, that is, a number of them can be derived as special cases under the assumption of failure independence. Our future research is focused on developing more specific and detailed models within this framework, as well as statistical inference procedures for performing estimations and predictions based on the experimental data.