Publications

ZORA Publication List

Publications

• 2026

  • Titov, S., Grotov, K., Sarasua Garmendia, C., Golubev, Y., Ramasamy, D., Bacchelli, A., Bernstein, A., & Bryksin, T. (2026). Observing fine-grained changes in Jupyter notebooks during development time Journal of Systems and Software, 241, 112983. https://doi.org/10.1016/j.jss.2026.112983
  • Singh, N., Sovrano, F., Hellendoorn, V., & Bacchelli, A. (2026). The Effect of Complexity and Provenance on Code Review Decisions: Evidence from a Controlled Experiment (FSE). 3, 3582–3603. https://doi.org/10.1145/3808165

• 2025

  • Pirouzkhah, S., Rani, P., Sovrano, F., Hellendoorn, V., & Bacchelli, A. (2025). The price of precision: the cost of preprocessing for automated code revision in code review Empirical Software Engineering, 31, 47. https://doi.org/10.1007/s10664-025-10781-4
  • Bourcier, V., Rani, P., Santander, M. I. W., Bacchelli, A., & Costiou, S. (2025). Empirically Evaluating the Impact of Object-Centric Breakpoints on the Debugging of Object-Oriented Programs (Vol. 2, FSE). FSE042. https://doi.org/10.1145/3715759
  • Sovrano, F., Vonlanthen, S., & Bacchelli, A. (2025). Beyond the lab: An in-depth analysis of real-world practices in government-to-citizen software user documentation Information and Software Technology, 181, 107676. https://doi.org/10.1016/j.infsof.2025.107676

• 2024

  • Rani, P., Petrulio, F., & Bacchelli, A. (2024). On Refining the SZZ Algorithm with Bug Discussion Data Empirical Software Engineering, 29, 115. https://doi.org/10.1007/s10664-024-10511-2
  • Rani, P., Zellweger, J., Kousadianos, V., Cruz, L., Kehrer, T., & Bacchelli, A. (2024). Energy Patterns for Web: An Exploratory Study Proceedings of the International Conference on Software Engineering, 12–22. https://doi.org/10.1145/3639475.3640110
  • Sovrano, F., Lognoul, M., & Bacchelli, A. (2024). An Empirical Study on Compliance with Ranking Transparency in the Software Documentation of EU Online Platforms Proceedings of the International Conference on Software Engineering, 46–56. https://doi.org/10.1145/3639475.3640112

• 2023

  • Yang, L., Xu, J., Zhang, Y., Zhang, H., & Bacchelli, A. (2023). EvaCRC: Evaluating Code Review Comments 275–287. https://doi.org/10.1145/3611643.3616245
  • Sovrano, F., Ashley, K., & Bacchelli, A. (2023). Toward Eliminating Hallucinations: GPT-based Explanatory AI for Intelligent Textbooks and Documentation CEUR Workshop Proceedings, 54–65. https://ceur-ws.org/Vol-3444/itb23_s3p2.pdf
  • Ramasamy, D., Sarasua, C., Bacchelli, A., & Bernstein, A. (2023). Visualising data science workflows to support third-party notebook comprehension: an empirical study Empirical Software Engineering, 28, 58. https://doi.org/10.1007/s10664-023-10289-9
  • Wurzel Gonçalves, P., Calikli, G., Serebrenik, A., & Bacchelli, A. (2023). Competencies for Code Review Proceedings of the ACM on Human-Computer Interaction, 7, 38. https://doi.org/10.1145/3579471
  • Ritschel, N., Sawant, A. A., Weintrop, D., Holmes, R., Bacchelli, A., Garcia, R., Chandrika, K. R., Mandal, A., Francis, P., & Shepherd, D. C. (2023). Training industrial end‐user programmers with interactive tutorials Software: Practice and Experience, 53, 729–747. https://doi.org/10.1002/spe.3167
  • Yang, L., Liu, B., Jia, J., Xue, J., Xu, J., Bacchelli, A., & Zhang, H. (2023). Evaluating Learning-to-Rank Models for Prioritizing Code Review Requests using Process Simulation Proceedings of Th IEEE International Conference on Software Analysis, Evolution and Reengineering, 461–472. https://doi.org/10.1109/saner56733.2023.00050
  • Fregnan, E., Fröhlich, J., Spadini, D., & Bacchelli, A. (2023). Graph-based visualization of merge requests for code review Journal of Systems and Software, 195, 111506. https://doi.org/10.1016/j.jss.2022.111506

• 2022

  • Braz, L., & Bacchelli, A. (2022). Software security during modern code review: The developer’s perspective 810–821. https://doi.org/10.1145/3540250.3549135
  • Fregnan, E., Braz, L., D’Ambros, M., Çalıklı, G., & Bacchelli, A. (2022). First come first served: The impact of file position on code review 483–494. https://doi.org/10.1145/3540250.3549177
  • Braz, L., Fregnan, E., Arora, V., & Bacchelli, A. (2022). An Exploratory Study on Regression Vulnerabilities (F. Madeiral, C. Lassenius, T. Conte, & T. Männistö, Eds.; pp. 12–22). ACM. https://doi.org/10.1145/3544902.3546250
  • Fregnan, E., Petrulio, F., & Bacchelli, A. (2022). The evolution of the code during review: an investigation on review changes Empirical Software Engineering, 27, 177:1-177:49. https://doi.org/10.1007/s10664-022-10205-7
  • Braz, L., Aeberhard, C., Çalikli, G., & Bacchelli, A. (2022). Less is more: Supporting developers in vulnerability detection during code review 1317–1329. https://doi.org/10.1145/3510003.3511560

Pagination