Chidambaram, N., Mens, T., & Decan, A. (2024). RABBIT: A tool for identifying bot accounts based on their recent GitHub event history. In 21st International Conference on Mining Software Repositories (pp. 5). Lisbon, Portugal: ACM. Peer reviewed |
Chidambaram, N., Decan, A., & Mens, T. (12 June 2023). Distinguishing Bots From Human Developers Based on Their GitHub Activity Types. CEUR Workshop Proceedings, 3483, 31-39. Peer reviewed |
Chidambaram, N., Decan, A., & Mens, T. (2023). A Dataset of Bot and Human Activities in GitHub. In Proceedings of the 20th International Conference on Mining Software Repositories (MSR 2023). IEEE. doi:10.1109/MSR59073.2023.00070 Peer reviewed |
Chidambaram, N., & Rostami Mazrae, P. (2022). Bot Detection in GitHub Repositories. In the Hackathon track of the 19th International Conference on Mining Software Repositories (MSR ’22). ACM. doi:10.1145/3524842.3528520 Peer reviewed |
Golzadeh, M., Mens, T., Decan, A., Constantinou, E., & Chidambaram, N. (26 May 2022). Recognizing bot activity in collaborative software development. IEEE Software, 39 (5), 56-61. doi:10.1109/ms.2022.3178601 Peer Reviewed verified by ORBi |
Golzadeh, M., Decan, A., & Chidambaram, N. (2022). On the Accuracy of Bot Detection Techniques. In 4th Workshop on Bots in Software Engineering (BotSE), IEEE/ACM ICSEW 2022. ACM. doi:10.1145/3528228.3528406 Peer reviewed |
Chidambaram, N., Decan, A., & Golzadeh, M. (2022). Leveraging Predictions From Multiple Repositories to Improve Bot Detection. In 4th Workshop on Bots in Software Engineering (BotSE), IEEE/ACM ICSEW 2022. IEEE. doi:10.1145/3528228.3528403 Peer reviewed |