GitRank: A Framework to Rank GitHub Repositories
This work addresses the need for quality assessment in open-source repositories to improve AI-based systems in software engineering, but it appears incremental as it builds on existing tools and measures.
The authors tackled the problem of evaluating the quality of open-source repositories, which is not directly available on platforms like GitHub, by developing GitRank, a framework that ranks repositories based on three criteria using code quality measures and the GrimoireLab toolkit, with preliminary evaluation results discussed.
Open-source repositories provide wealth of information and are increasingly being used to build artificial intelligence (AI) based systems to solve problems in software engineering. Open-source repositories could be of varying quality levels, and bad-quality repositories could degrade performance of these systems. Evaluating quality of open-source repositories, which is not available directly on code hosting sites such as GitHub, is thus important. In this hackathon, we utilize known code quality measures and GrimoireLab toolkit to implement a framework, named GitRank, to rank open-source repositories on three different criteria. We discuss our findings and preliminary evaluation in this hackathon report.