Print Email Facebook Twitter The effects of change decomposition on code review—a controlled experiment Title The effects of change decomposition on code review—a controlled experiment Author di Biase, M. (TU Delft Software Engineering; Software Improvement Group) Bruntink, Magiel (Software Improvement Group) van Deursen, A. (TU Delft Software Technology) Bacchelli, A. (University of Zürich) Department Software Technology Date 2019-05-13 Abstract Background: Code review is a cognitively demanding and time-consuming process. Previous qualitative studies hinted at how decomposing change sets into multiple yet internally coherent ones would improve the reviewing process. So far, literature provided no quantitative analysis of this hypothesis.Aims: (1) Quantitatively measure the effects of change decomposition on the outcome of code review (in terms of number of found defects, wrongly reported issues, suggested improvements, time, and understanding); (2) Qualitatively analyze how subjects approach the review and navigate the code, building knowledge and addressing existing issues, in large vs. decomposed changes.Method: Controlled experiment using the pull-based development model involving 28 software developers among professionals and graduate students.Results: Change decomposition leads to fewer wrongly reported issues, influences how subjects approach and conduct the review activity (by increasing context- seeking), yet impacts neither understanding the change rationale nor the number of found defects.Conclusions: Change decomposition reduces the noise for subsequent data analyses but also significantly supports the tasks of the developers in charge of reviewing the changes. As such, commits belonging to different concepts should be separated, adopting this as a best practice in software engineering. Subject Code reviewControlled experimentChange decompositionPull-based development model To reference this document use: http://resolver.tudelft.nl/uuid:2a414f72-6d6e-4c51-a7f8-7f789c25dd73 DOI https://doi.org/10.7717/peerj-cs.193 ISSN 2376-5992 Source PeerJ Computer Science, 5, 1-25 Part of collection Institutional Repository Document type journal article Rights © 2019 M. di Biase, Magiel Bruntink, A. van Deursen, A. Bacchelli Files PDF cs_193.pdf 1.63 MB Close viewer /islandora/object/uuid:2a414f72-6d6e-4c51-a7f8-7f789c25dd73/datastream/OBJ/view