Publications

ZORA Publication List

Publications

• 2022

  • Gonçalves, P. W., Fregnan, E., Baum, T., Schneider, K., & Bacchelli, A. (2022). Do explicit review strategies improve code review performance? Towards understanding the role of cognitive load Empirical Software Engineering, 27, 99:1-99:46. https://doi.org/10.1007/s10664-022-10123-8
  • Fregnan, E., Petrulio, F., Di Geronimo, L., & Bacchelli, A. (2022). What happens in my code reviews? An investigation on automatically classifying review changes Empirical Software Engineering, 27, 89:1-89:43. https://doi.org/10.1007/s10664-021-10075-5
  • Wurzelová, P., Çalikli, G., & Bacchelli, A. (2022). Interpersonal Conflicts During Code Review 25th ACM Conference On Computer-Supported Cooperative Work And Social Computing, Taipei. https://doi.org/10.5281/zenodo.5848794
  • Ramasamy, D., Sarasua, C., Bacchelli, A., & Bernstein, A. (2022). Workflow analysis of data science code in public GitHub repositories Empirical Software Engineering, 28, 7. https://doi.org/10.1007/s10664-022-10229-z

• 2021

  • Gasparini, L., Fregnan, E., Braz, L., Baum, T., & Bacchelli, A. (2021). ChangeViz: Enhancing the GitHub Pull Request Interface with Method Call Information 115–119. https://doi.org/10.1109/VISSOFT52517.2021.00022
  • Petrulio, F., Sawant, A. A., & Bacchelli, A. (2021). The indolent lambdification of Java: Understanding the support for lambda expressions in the Java ecosystem Empirical Software Engineering, 26, 134:1-134:36. https://doi.org/10.1007/s10664-021-10039-9
  • Bogomolov, E., Kovalenko, V., Rebryk, Y., Bacchelli, A., & Bryksin, T. (2021). Authorship attribution of source code: a language-agnostic approach and applicability in software engineering 932–944. https://doi.org/10.1145/3468264.3468606
  • Braz, L., Fregnan, E., Çalikli, G., & Bacchelli, A. (2021). Why Don’t Developers Detect Improper Input Validation? 499–511. https://doi.org/10.1109/ICSE43902.2021.00054

• 2020

  • Spadini, D., Çalikli, G., & Bacchelli, A. (2020). Primers or reminders? The effects of existing review comments on code review 1171–1182. https://doi.org/10.1145/3377811.3380385
  • Spadini, D., Schvarcbacher, M., Oprescu, A.-M., Bruntink, M., & Bacchelli, A. (2020). Investigating Severity Thresholds for Test Smells 311–321. https://doi.org/10.1145/3379597.3387453
  • Gonçalves, P. W., Fregnan, E., Baum, T., Schneider, K., & Bacchelli, A. (2020). Do Explicit Review Strategies Improve Code Review Performance? 606–610. https://doi.org/10.1145/3379597.3387509
  • Di Geronimo, L., Braz, L., Fregnan, E., Palomba, F., & Bacchelli, A. (2020). UI Dark Patterns and Where to Find Them A Study on Mobile Applications and User Perception 1–14. https://doi.org/10.1145/3313831.3376600
  • di Biase, M., Bruntink, M., van Deursen, A., & Bacchelli, A. (2020). The effects of change decomposition on code review—a controlled experiment PeerJ, 5, 193–193. https://doi.org/10.7717/peerj-cs.193
  • Pascarella, L., Palomba, F., & Bacchelli, A. (2020). On the performance of method-level bug prediction: A negative result Journal of Systems and Software, 161, 110493. https://doi.org/10.1016/j.jss.2019.110493
  • Kovalenko, V., Tintarev, N., Pasynkov, E., Bird, C., & Bacchelli, A. (2020). Does Reviewer Recommendation Help Developers? IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, 710–731. https://doi.org/10.1109/TSE.2018.2868367
  • Sawant, A. A., Robbes, R., & Bacchelli, A. (2020). To react, or not to react: Patterns of reaction to API deprecation Empirical Software Engineering, 24, 3824–3870. https://doi.org/10.1007/s10664-019-09713-w

• 2019

  • Eck, M., Palomba, F., Castelluccio, M., & Bacchelli, A. (2019). Understanding flaky tests: the developer’s perspective 830–840. https://doi.org/10.1145/3338906.3338945
  • Kovalenko, V., Bogomolov, E., Bryksin, T., & Bacchelli, A. (2019). PathMiner: A Library for Mining of Path-Based Representations of Code 13–17. https://doi.org/10.1109/MSR.2019.00013
  • Spadini, D., Palomba, F., Baum, T., Hanenberg, S., Bruntink, M., & Bacchelli, A. (2019). Test-Driven Code Review: An Empirical Study 1061–1072. https://doi.org/10.1109/ICSE.2019.00110
  • Vassallo, C., Grano, G., Palomba, F., Gall, H. C., & Bacchelli, A. (2019). A large-scale empirical exploration on refactoring activities in open source software projects Science of Computer Programming, 180, 1–15. https://doi.org/10.1016/j.scico.2019.05.002

Pagination