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@inproceedings{1417429,
author = {Lipčák, Jakub and Rossi, Bruno},
address = {Not specified},
booktitle = {44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018},
doi = {http://dx.doi.org/10.1109/SEAA.2018.00068},
keywords = {Source Code Reviewer Recommendation; Distributed Software Development; Mining Software Repositories},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Not specified},
isbn = {978-1-5386-7383-6},
pages = {378-387},
publisher = {IEEE},
title = {A Large-Scale Study on Source Code Reviewer Recommendation},
url = {https://ieeexplore.ieee.org/document/8498235},
year = {2018}
}
TY - JOUR
ID - 1417429
AU - Lipčák, Jakub - Rossi, Bruno
PY - 2018
TI - A Large-Scale Study on Source Code Reviewer Recommendation
PB - IEEE
CY - Not specified
SN - 9781538673836
KW - Source Code Reviewer Recommendation
KW - Distributed Software Development
KW - Mining Software Repositories
UR - https://ieeexplore.ieee.org/document/8498235
N2 - Context: Software code reviews are an important part of the development process, leading to better software quality and reduced overall costs. However, finding appropriate code reviewers is a complex and time-consuming task. Goals: In this paper, we propose a large-scale study to compare performance of two main source code reviewer recommendation algorithms (RevFinder, Naive Bayes-based) in identifying the best code reviewers for opened pull requests. Method: We mined data from Github and Gerrit repositories, building a large dataset of 51 projects, with more than 293K pull requests analyzed, 180K owners and 157K reviewers. Results: Based on the large analysis, we can state that i) no model can be generalized as best for all projects, ii) the usage of different repository (Gerrit, GitHub) has a large impact on the the recommendation results, iii) exploiting sub-projects information available in Gerrit improves the recommendation results.
ER -
LIPČÁK, Jakub a Bruno ROSSI. A Large-Scale Study on Source Code Reviewer Recommendation. Online. In \textit{44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018}. Not specified: IEEE, 2018, s.~378-387. ISBN~978-1-5386-7383-6. Dostupné z: https://dx.doi.org/10.1109/SEAA.2018.00068.
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