GitRank: A Framework to Rank GitHub Repositories
Niranjan Hasabnis

TL;DR
GitRank is a framework that ranks GitHub repositories based on quality measures using the GrimoireLab toolkit, aiding in selecting high-quality open-source projects for AI and software engineering applications.
Contribution
This paper introduces GitRank, a novel framework that evaluates and ranks open-source repositories on multiple quality criteria, leveraging known metrics and the GrimoireLab toolkit.
Findings
Effective ranking of repositories based on quality measures
Preliminary evaluation shows promising results
Framework aids in selecting high-quality open-source projects
Abstract
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBiomedical and Engineering Education · Scientific Computing and Data Management · Genetics, Bioinformatics, and Biomedical Research
