The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
La révision de code moderne est une pratique bien connue pour évaluer la qualité des logiciels, dans laquelle les développeurs discutent de la qualité dans un outil de révision basé sur le Web. Cependant, cette approche légère peut entraîner une participation inefficace à l'évaluation, en particulier lorsque les commentaires deviennent soit excessifs (c'est-à-dire trop nombreux), soit décevants (c'est-à-dire trop peu nombreux). Dans cette étude, nous étudions le phénomène des commentaires des évaluateurs. Grâce à une analyse empirique à grande échelle de plus de 1.1 million d'avis provenant de cinq systèmes OSS, nous menons une étude exploratoire pour étudier la fréquence, la taille et l'évolution des commentaires des évaluateurs. De plus, nous menons également une étude de modélisation pour comprendre les caractéristiques les plus importantes qui pourraient potentiellement susciter les commentaires des évaluateurs. Nos résultats révèlent que (i) le nombre de commentaires et le nombre de mots dans les commentaires ont tendance à varier selon les critiques et les systèmes étudiés ; (ii) les évaluateurs modifient leurs comportements en matière de commentaires au fil du temps ; et (iii) l'expérience humaine et les aspects relatifs à la propriété des correctifs ont un impact sur le nombre de commentaires et le nombre de mots dans les commentaires.
Toshiki HIRAO
Nara Institute of Science and Technology
Raula GAIKOVINA KULA
Nara Institute of Science and Technology
Akinori IHARA
Wakayama University
Kenichi MATSUMOTO
Nara Institute of Science and Technology
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copier
Toshiki HIRAO, Raula GAIKOVINA KULA, Akinori IHARA, Kenichi MATSUMOTO, "Understanding Developer Commenting in Code Reviews" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 12, pp. 2423-2432, December 2019, doi: 10.1587/transinf.2019MPP0005.
Abstract: Modern code review is a well-known practice to assess the quality of software where developers discuss the quality in a web-based review tool. However, this lightweight approach may risk an inefficient review participation, especially when comments becomes either excessive (i.e., too many) or underwhelming (i.e., too few). In this study, we investigate the phenomena of reviewer commenting. Through a large-scale empirical analysis of over 1.1 million reviews from five OSS systems, we conduct an exploratory study to investigate the frequency, size, and evolution of reviewer commenting. Moreover, we also conduct a modeling study to understand the most important features that potentially drive reviewer comments. Our results find that (i) the number of comments and the number of words in the comments tend to vary among reviews and across studied systems; (ii) reviewers change their behaviours in commenting over time; and (iii) human experience and patch property aspects impact the number of comments and the number of words in the comments.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019MPP0005/_p
Copier
@ARTICLE{e102-d_12_2423,
author={Toshiki HIRAO, Raula GAIKOVINA KULA, Akinori IHARA, Kenichi MATSUMOTO, },
journal={IEICE TRANSACTIONS on Information},
title={Understanding Developer Commenting in Code Reviews},
year={2019},
volume={E102-D},
number={12},
pages={2423-2432},
abstract={Modern code review is a well-known practice to assess the quality of software where developers discuss the quality in a web-based review tool. However, this lightweight approach may risk an inefficient review participation, especially when comments becomes either excessive (i.e., too many) or underwhelming (i.e., too few). In this study, we investigate the phenomena of reviewer commenting. Through a large-scale empirical analysis of over 1.1 million reviews from five OSS systems, we conduct an exploratory study to investigate the frequency, size, and evolution of reviewer commenting. Moreover, we also conduct a modeling study to understand the most important features that potentially drive reviewer comments. Our results find that (i) the number of comments and the number of words in the comments tend to vary among reviews and across studied systems; (ii) reviewers change their behaviours in commenting over time; and (iii) human experience and patch property aspects impact the number of comments and the number of words in the comments.},
keywords={},
doi={10.1587/transinf.2019MPP0005},
ISSN={1745-1361},
month={December},}
Copier
TY - JOUR
TI - Understanding Developer Commenting in Code Reviews
T2 - IEICE TRANSACTIONS on Information
SP - 2423
EP - 2432
AU - Toshiki HIRAO
AU - Raula GAIKOVINA KULA
AU - Akinori IHARA
AU - Kenichi MATSUMOTO
PY - 2019
DO - 10.1587/transinf.2019MPP0005
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2019
AB - Modern code review is a well-known practice to assess the quality of software where developers discuss the quality in a web-based review tool. However, this lightweight approach may risk an inefficient review participation, especially when comments becomes either excessive (i.e., too many) or underwhelming (i.e., too few). In this study, we investigate the phenomena of reviewer commenting. Through a large-scale empirical analysis of over 1.1 million reviews from five OSS systems, we conduct an exploratory study to investigate the frequency, size, and evolution of reviewer commenting. Moreover, we also conduct a modeling study to understand the most important features that potentially drive reviewer comments. Our results find that (i) the number of comments and the number of words in the comments tend to vary among reviews and across studied systems; (ii) reviewers change their behaviours in commenting over time; and (iii) human experience and patch property aspects impact the number of comments and the number of words in the comments.
ER -