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Evaluating a Bot Detection Model on Git Commit Messages.

, , and . BENEVOL, volume 2912 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)

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A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments., , , and . CoRR, (2020)Evaluating a bot detection model on git commit messages., , and . CoRR, (2021)On the Effect of Discussions on Pull Request Decisions., , and . BENEVOL, volume 2605 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)On the usage, co-usage and migration of CI/CD tools: A qualitative analysis., , , and . Empir. Softw. Eng., 28 (2): 52 (March 2023)Identifying bot activity in GitHub pull request and issue comments., , , and . BotSE@ICSE, page 21-25. IEEE, (2021)A new Ensemble based multi-agent system for prediction problems: Case study of modeling coal free swelling index., , and . Appl. Soft Comput., (2018)A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments., , , and . J. Syst. Softw., (2021)On the rise and fall of CI services in GitHub., , and . SANER, page 662-672. IEEE, (2022)Leveraging predictions from multiple repositories to improve bot detection., , and . BotSE@ICSE, page 6-9. ACM, (2022)On the Use of GitHub Actions in Software Development Repositories., , , and . ICSME, page 235-245. IEEE, (2022)