Who should make decision on this pull request? Analyzing time-decaying relationships and file similarities for integrator prediction

Author

Jing JIANG, Beijing University of Aeronautics and Astronautics (Beihang University)
David LO, Singapore Management UniversityFollow
Jiateng ZHENG, Beijing University of Aeronautics and Astronautics (Beihang University)
Xin XIA, Monash University
Yun YANG, Beijing University of Aeronautics and Astronautics (Beihang University)
Li ZHANG, Beijing University of Aeronautics and Astronautics (Beihang University)

Publication Type

Journal Article

Version

publishedVersion

Publication Date

8-2019

Abstract

In pull-based development model, integrators are responsible for making decisions about whether to accept pull requests andintegrate code contributions. Ideally, pull requests are assigned to integrators and evaluated within a short time after their submissions. However, the volume of incoming pull requests is large in popular projects, and integrators often encounter difficulties inprocessing pull requests in a timely fashion. Therefore, an automatic integrator prediction approach is required to assign appropriate pull requests to integrators. In this paper, we propose an approach TRFPre which analyzes Time-decaying Relationships andFile similarities to predict integrators. We evaluate the effectiveness of TRFPre on 24 projects containing 138,373 pull requests.Experimental results show that TRFPre makes accurate integrator predictions in terms of accuracies and Mean Reciprocal Rank.Less than 2 predictions are needed to find correct integrator in 91.67% of projects. In comparison with state-of-the-art approachescHRev, WRC, TIE, CoreDevRec and ACRec, TRFPre improves top-1 accuracy by 68.2%, 73.9%, 49.3%, 14.3% and 46.4% onaverage across 24 projects.

Keywords

Integrator prediction, Code review, Open source, GitHub

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Journal of Systems and Software

Volume

154

First Page

196

Last Page

210

ISSN

0164-1212

Identifier

10.1016/j.jss.2019.04.055

Publisher

Elsevier

Citation

JIANG, Jing; LO, David; ZHENG, Jiateng; XIA, Xin; YANG, Yun; and ZHANG, Li. Who should make decision on this pull request? Analyzing time-decaying relationships and file similarities for integrator prediction. (2019). Journal of Systems and Software. 154, 196-210.
Available at: https://ink.library.smu.edu.sg/sis_research/4345

Copyright Owner and License

Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

https://doi.org/10.1016/j.jss.2019.04.055