Software reliability is of utmost importance in today’s technology-driven world, where software systems play a critical role in various domains. Ensuring the reliability of software is essential to avoid costly failures, user dissatisfaction, and potential risks. This research addresses the challenges of uncertain operating environments and the need to consider both testing coverage and uncertainties simultaneously in software reliability modeling. By developing a software reliability growth model (SRGM) that incorporates uncertainties using the gamma distribution and integrates testing coverage with a factor influencing fault detection effectiveness, this study provides a comprehensive framework for assessing and predicting software reliability in real-world scenario. Moreover, organizations must consider the cost implications and strike a balance between reliability and time-to-market constraints. This paper also extends the analysis to calculate the optimal release time, providing practical guidance for determining the most opportune moment to release the software while considering both reliability objectives and resource constraints.
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