Towards a taxonomy of code review smells

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buir.advisorTüzün, Eray
dc.contributor.authorDoğan, Emre
dc.date.accessioned2020-10-12T05:56:05Z
dc.date.available2020-10-12T05:56:05Z
dc.date.copyright2020-09
dc.date.issued2020-09
dc.date.submitted2020-10
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2020.en_US
dc.descriptionIncludes bibliographical references (leaves 51-59).en_US
dc.description.abstractCode review is a crucial step of the software development life cycle in order to detect possible problems in source code before merging the changeset to the codebase. Although there is no consensus on a formally defined life cycle of the code review process, many companies and open source software (OSS) communities converge on common rules and best practices. In spite of minor differences in different platforms, the primary purpose of all these rules and practices is to lead a faster and more effective code review process. Non-conformance of developers to this process does not only hinder the advantages of the code review but can also negatively affect the other steps of the software development life cycle. The aim of this study is to provide an empirical understanding of the bad practices followed in the code review process, that are code review (CR) smells. To this end, we first conduct a multivocal literature review in order to gather code review bad practices discussed in white and gray literature. Then, we conduct a survey with 32 experienced software practitioners and perform follow-up interviews in order to get their expert opinion. Based on the multivocal literature review and expert opinion of experienced developers, a taxonomy of code review smells (lack of code review, review buddies, reviewer-author ping pong, looks good to me (LGTM) reviews, sleeping reviews, missing context in reviews and large changesets) is introduced. To quantitatively demonstrate the existence of these smells, we analyze 283,354 code reviews collected from eight OSS projects. We observe that a considerable number of code review smells exist in all projects with varying degree of ratios.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2020-10-12T05:56:05Z No. of bitstreams: 1 10361684.pdf: 2118744 bytes, checksum: a862d4d7f11cd08eaeb3ecdba4e8e4d3 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-10-12T05:56:05Z (GMT). No. of bitstreams: 1 10361684.pdf: 2118744 bytes, checksum: a862d4d7f11cd08eaeb3ecdba4e8e4d3 (MD5) Previous issue date: 2020-10en
dc.description.statementofresponsibilityby Emre Doğanen_US
dc.embargo.release2021-04-08
dc.format.extentx, 62 leaves : charts (some color) ; 30 cm.en_US
dc.identifier.itemidB122041
dc.identifier.urihttp://hdl.handle.net/11693/54183
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectModern code reviewen_US
dc.subjectBad practicesen_US
dc.subjectConformance checkingen_US
dc.subjectCode review smellsen_US
dc.titleTowards a taxonomy of code review smellsen_US
dc.title.alternativeKod gözden geçirme sürecindeki kötü uygulamaların sınıflandırılmasıen_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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