@proceedings {1769, title = {Investigating Code Review Practices in Defective Files: An Empirical Study of the Qt System}, year = {2015}, month = {05/2015}, publisher = {IEEE}, abstract = {Software code review is a well-established software quality practice. Recently, Modern Code Review (MCR) has been widely adopted in both open source and proprietary projects. To evaluate the impact that characteristics of MCR practices have on software quality, this paper comparatively studies MCR practices in defective and clean source code files. We investigate defective files along two perspectives: 1) files that will eventually have defects (i.e., future-defective files) and 2) files that have historically been defective (i.e., risky files). Through an empirical study of 11,736 reviews of changes to 24,486 files from the Qt open source project, we find that both future-defective files and risky files tend to be reviewed less rigorously than their clean counterparts. We also find that the concerns addressed during the code reviews of both defective and clean files tend to enhance evolvability, i.e., ease future maintenance (like documentation), rather than focus on functional issues (like incorrect program logic). Our findings suggest that although functionality concerns are rarely addressed during code review, the rigor of the reviewing process that is applied to a source code file throughout a development cycle shares a link with its defect proneness.}, keywords = {code review, software quality}, url = {http://sail.cs.queensu.ca/publications/pubs/msr2015-thongtanunam.pdf}, attachments = {https://flosshub.org/sites/flosshub.org/files/msr2015-thongtanunam.pdf}, author = {Patanamon Thongtanunam and McIntosh, Shane and Hassan, Ahmed E. and Hajimu Iida} } @proceedings {1498, title = {Who Does What during a Code Review? Datasets of OSS Peer Review Repositories }, year = {2013}, month = {05/2013}, abstract = {We present four datasets that are focused on the general roles of OSS peer review members. With data mined from both an integrated peer review system and code source repositories, our rich datasets comprise of peer review data that was automatically recorded. Using the Android project as a case study, we describe our extraction methodology, the datasets and their application used for three separate studies. Our datasets are available online at http://sdlab.naist.jp/reviewmining/}, keywords = {android, case study, code review, data set, peer review, roles, source code}, author = {Kazuki Hamasaki and Raula Gaikovina Kula and Norihiro Yoshida and A. E. Camargo Cruz and Kenji Fujiwara and Hajimu Iida} }