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Modeling and Assessing Software Reliability in Open-Source Projects
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DOI：10.3390/computation13090214.png)
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Abstract
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One of the key components of the software quality model is reliability. Its importance has grown with the increasing use and reuse of open-source components in software development. Software reliability growth models are commonly employed to address this aspect by predicting future failure rates and estimating the number of remaining defects throughout the development process. This paper investigates two software reliability growth models derived from the Verhulst model, with a particular focus on a structural property known as Hausdorff saturation. We provide analytical estimates for this characteristic and propose it as an additional criterion for model selection. The models are evaluated using four open-source datasets, where the Hausdorff saturation metric supports the conclusions drawn from standard goodness-of-fit measures. Furthermore, we introduce an interactive software reliability assessment tool that integrates with GitHub, enabling expert users to analyze real-time issue-tracking data from open-source repositories. The tool facilitates model comparison and enhances practical applicability. Overall, the proposed approach contributes to more robust reliability assessment by combining theoretical insights with actionable diagnostics.
Keywords:
software reliability growth model
non-homogeneous Poisson process (NHPP)
Hausdorff saturation
open-source projects
reliability assessment tool
GitHub
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