Analysis of software fault removal policies using a non-homogeneous continuous time Markov chain

Software reliability is an important metric that quantifies the quality of a software product and is inversely related to the residual number of faults in the system. Fault removal is a critical process in achieving desired level of quality before software deployment in the field. Conventional software reliability models assume that the time to remove a fault is negligible and that the fault removal process is perfect. In this paper we examine various kinds of fault removal policies, and analyze their effect on the residual number of faults at the end of the testing process, using a non-homogeneous continuous time Markov chain. The fault removal rate is initially assumed to be constant, and it is subsequently extended to cover time and state dependencies. We then extend the non-homogeneous continuous time Markov chain (NHCTMC) framework to include imperfections in the fault removal process. A method to compute the failure intensity of the software in the presence of explicit fault removal is also proposed. The fault removal scenarios can be easily incorporated using the state-space view of the non-homogeneous Poisson process.