Non-homogeneous Poisson process software reliability and cost models with testing coverage

This paper proposes a software reliability model that incorporates testing coverage information. Testing coverage is very important for both software developers and customers of software products. For developers, testing coverage information helps them to evaluate how much effort has been spent and how much more is needed. For customers, this information estimates the confidence of using the software product. Although research has been conducted and software reliability models have been developed, some practical issues have not been addressed. Testing coverage is one of these issues. The model is developed based on a non-homogeneous Poisson process (NHPP) and can be used to estimate and predict the reliability of software products quantitatively. We examine the goodness-of-fit of this proposed model and present the results using several sets of software testing data. Comparisons of this model and other existing NHPP models are made. We find that the new model can provide a significant improved goodness-of-fit and estimation power. A software cost model incorporating testing coverage is also developed. Besides some traditional cost items such as testing cost and error removal cost, risk cost due to potential faults in the uncovered code is also included associated with the number of demands from customers. Optimal release policies that minimize the expected total cost subject to the reliability requirement are developed.