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Personal profile

Research profile

My research field is empirical software engineering. My current vision is to support software peer code review, developing a deep scientific understanding of this process to move code review away from decisions based on intuition, or activities painstakingly conducted manually, into solutions created using data-driven mathematical models, which exploit the large amount of information available during the software engineering and review process.

My research has advanced the fundamentals of software analytics, especially to mine unstructured software data, and the peer code review process. The techniques and methods I develop and use are at the intersection of software engineering, information retrieval, data mining, machine learning, and social science.

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Research Output

  • 44 Conference contribution
  • 12 Article
  • 1 Chapter
  • 1 Foreword/postscript

On the performance of method-level bug prediction: A negative result

Pascarella, L., Palomba, F. & Bacchelli, A., 2020, In : Journal of Systems and Software. 161, p. 1-15 15 p., 110493.

Research output: Contribution to journalArticleScientificpeer-review

  • Primers or Reminders? The Effects of Existing Review Comments on Code Review

    Spadini, D., Calikli, G. & Bacchelli, A., 2020, Proceedings of the 42nd International Conference on Software Engineering (ICSE '20). 12 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    File
  • 299 Downloads (Pure)

    Classifying code comments in Java software systems

    Pascarella, L., Bruntink, M. & Bacchelli, A., 2019, In : Empirical Software Engineering. 24, 3, p. 1499-1537 39 p.

    Research output: Contribution to journalArticleScientificpeer-review

    Open Access
    File
  • 5 Citations (Scopus)
    70 Downloads (Pure)

    Does reviewer recommendation help developers?

    Kovalenko, V., Tintarev, N., Pasynkov, E., Bird, C. & Bacchelli, A., 2019, In : IEEE Transactions on Software Engineering. p. 1-23 23 p.

    Research output: Contribution to journalArticleScientificpeer-review

    Open Access
    File
  • 158 Downloads (Pure)

    Fine-grained just-in-time defect prediction

    Pascarella, L., Palomba, F. & Bacchelli, A., 2019, In : Journal of Systems and Software. 150, p. 22-36 15 p.

    Research output: Contribution to journalArticleScientificpeer-review

  • 8 Citations (Scopus)

    Datasets

    Large scale API Usage dataset

    Sawant, A. A. (Creator), Bacchelli, A. (Contributor) & Robbes, R. (Creator), TU Delft - 4TU Centre for research data, 2019

    Dataset

    The Effects of Change Decomposition on Code Review - A Controlled Experiment - Online appendix

    di Biase, M. (Creator), Bacchelli, A. (Contributor), Bruntink, M. (Contributor) & van Deursen, A. (Contributor), TU Delft - 4TU Centre for research data, 2018

    Dataset

    Prizes

    CSCW 2015 ACM SIGCHI Best Paper Award

    A Guzzi (Recipient), Bacchelli, A. (Recipient), Yann Riche (Recipient) & van Deursen, A. (Recipient), 15 Mar 2015

    Prize: Prize (including medals and awards)