This paper presents a unified approach to model the reliability growth of software with imperfect debugging and coverage factor. Existing testing coverage‐based software reliability growth models considered that faults present at a particular fault location are detected with certainty during the testing process. Practically, it is very difficult to detect all software faults. To overcome this limitation, a revised software reliability growth model has been developed with the assumption that detection of the faults at a particular fault location is not definite. Furthermore, a new method to model the imperfect debugging phenomenon has been incorporated in the proposed study. A revised model ranking method has been developed to improve the accuracy of model ranking, which is mainly extension of existing normalized criteria distance method. Change point analysis has been done with the effect of different environmental factors on the models' parameters. Numerical examples are given to demonstrate the effectiveness of the proposed model.

This article presents a software reliability growth model based on non-homogeneous Poisson process. The main focus of this article is to deliver a method for software reliability modelling incorporating the concept of time-dependent fault introduction and fault removal rate with change point. Also in this article, a cost model with change point has been developed. Based on the cost model optimal release policy with change point has been discussed. Maximum likelihood technique has been applied to estimate the parameters of the model. The proposed model has been validated using some real software failure data. Comparison has been made with models incorporating change point and without change point. The application of the proposed cost model has been shown using some numerical examples.