A New Paradigm for Software Reliability Modeling – From NHPP to NHGP

Abstract

Non-homogeneous gamma process (NHGP) models with typical reliability growth patterns are developed for software reliability assessment in order to overcome a weak point of the usual non-homogeneous Poisson process (NHPP) models. Though the analytical treatment of NHGPs as stochastic point processes is not so easy in general, they have an advantage to involve the NHPPs as well as a gamma renewal process as special cases, and are rather tractable on parameter estimation by means of the method of maximum likelihood. We perform the goodness-of fit test for several NHGP-based software reliability models (SRMs) and compare them with the existing NHPP-based ones. Throughout a numerical example with a real software fault data, it is shown that the NHGP-based SRMs can provide the better goodness-of-fit performances in earlier testing phases than the NHPP-based ones, but approach to them gradually as the testing time goes on. This implies that our new software reliability modeling framework with flexibility can describe better the software-fault detection phenomenon when the less information on software fault data is available.