mlsanityData to 7 Oct 2026

GitRank: A Framework to Rank GitHub Repositories

arXiv 2205.02360 ↗First posted 4 May 2022cs.SE cs.AI cs.LGcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 6 of its 33 references that are in the map. First posted on arXiv 4 May 2022.

Builds on

6 of 33 references.

References · 6

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2020Unsupervised Translation of Programming Languagescited by 262
  3. 2020Graph-based, Self-Supervised Program Repair from Diagnostic Feedbackcited by 93
  4. 2018Aroma: Code Recommendation via Structural Code Searchcited by 29
  5. 2018What's in a GitHub Star? Understanding Repository Starring Practices in a Social Coding Platformcited by 25
  6. 2020ControlFlag: A Self-Supervised Idiosyncratic Pattern Detection System for Software Control Structurescited by 5

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Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1.

3 papers.