Over the past few decades, extensive research has been conducted on software reliability growth models based on the non-homogeneous Poisson process. However, most existing studies rely on the premise of perfect debugging, failing to fully consider key factors such as potential error introduction, the diversity of failure types, and dynamic changes in the testing environment. They also neglect the systematic analysis of the testing and repair processes. This disconnection between theoretical assumptions and practical application scenarios makes it difficult for these models to accurately depict the complex phenomena in real testing processes. To address these limitations, this study proposes an integrated NHPP-based SRGM combining an imperfect debugging mechanism, the fault detection process (FDP) and fault correction process (FCP), fault heterogeneity, and change-point analysis. The model introduces dynamic correction intensity linked to pending faults, classifies faults into simple (instantly corrected) and complex (queued for FCP), and models detection and correction rates as piecewise functions before and after change points, capturing realistic scheduling logic and synchronized effects of strategy, tools, and personnel changes. On this basis, a comprehensive and optimized software release strategy is further proposed. This strategy accounts for detection costs during testing, failure repair costs, and comprehensive costs from post-release failures. Its aim is to minimize full life cycle costs while meeting the reliability targets, thus providing software project managers with a scientifically grounded and practically reliable decision-making basis leveraging the integrated modeling innovations.
邱湘伊 et al. (Tue,) studied this question.