Towards comprehensive software reliability evaluation in open source software

This paper proposes a unified modeling framework for software reliability assessment in open source project. We combine the classical non-homogeneous Poisson process based software reliability growth model (SRGM) with a familiar regression scheme called the generalized linear model (GLM), and develop a novel framework not only to estimate software reliability measures, but also to investigate impacts of software metrics on the fault-detection process. The resulting GLM-based SRGM involves the common SRGMs as well as some existing metrics-based SRMs, such as logistic-regression-based SRGM and Poisson-regression-based SRGM, and possesses a great data fitting ability. We also provide an effective parameter estimation algorithm based on the EM (Expectation-Maximization) principle. Finally, it is shown through numerical experiments with actual open source project data that our approach can estimate software reliability measures with higher accuracy and can feedback the analysis results to improve the current software development projects.