Analyzing the impact of process smells in code review

buir.advisorTüzün, Eray
dc.contributor.authorPirouzkhah, Shirin
dc.date.accessioned2022-08-09T06:33:16Z
dc.date.available2022-08-09T06:33:16Z
dc.date.copyright2022-07
dc.date.issued2022-07
dc.date.submitted2022-07-07
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Master's): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2022.en_US
dc.descriptionIncludes bibliographical references (leaves 87-90).en_US
dc.description.abstractCode review is a valuable modern software development practice for identifying potential problems in changesets and improving source code quality in software projects. Developers adhere to specific rules and best practices in an ideal code review process. Deviations from these best practices can potentially lead to unin­tended consequences. These deviations, also known as code review process smells, affect different parts of the code review process and its outcomes. This research empirically analyzes the correlations between process smells, and the impact of code review process smells (shared knowledge, reopened issues, time to complete review (TTCR), abandoned pull requests (PRs), number or review comments, and contribution of large changeset reviewers). The relationship between smells and their impact is correlation-based, but a causal relationship is not guaranteed because proving such relationships is not straightforward. To quantitatively an­alyze the impact of smells in the code review process, we investigated 244,903 PRs from four open source software (OSS) projects from Gerrit (Qt, Eclipse, Wireshark, and LibreOffice). As a result, we discovered that the existence of a committers’ side smell in a pull request (PR) could lead to the occurrence of reviewers’ side smells in the same PR. We also observed that reviewers assigned repeatedly by the same author to review the PR have a heavier review workload. Furthermore, the ping pong reviews and large changesets are most likely to in­crease the bug reopen ratio. In addition, we noticed that the time to complete review of a smelly PR is likely to be more than time to complete review of non-smelly PR. Also, the existence of process smells in a PR effect the number of review comments in that pull request.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2022-08-09T06:33:16Z No. of bitstreams: 1 B161068.pdf: 8370240 bytes, checksum: 343a0245fcdd4aa5a0135246d0f5572e (MD5)en
dc.description.provenanceMade available in DSpace on 2022-08-09T06:33:16Z (GMT). No. of bitstreams: 1 B161068.pdf: 8370240 bytes, checksum: 343a0245fcdd4aa5a0135246d0f5572e (MD5) Previous issue date: 2022-07en
dc.description.statementofresponsibilityby Shirin Pirouzkhahen_US
dc.embargo.release2023-01-07
dc.format.extentxv, 90 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB161068
dc.identifier.urihttp://hdl.handle.net/11693/110400
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectModern code reviewen_US
dc.subjectProcess smellsen_US
dc.subjectCode review anti-patternsen_US
dc.subjectImpacts of anti-patternsen_US
dc.subjectImpact of process smellsen_US
dc.titleAnalyzing the impact of process smells in code reviewen_US
dc.title.alternativeKod inceleme sürecinde uygunsuzluk etkisinin analizien_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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