A review of code reviewer recommendation studies: Challenges and future directions

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buir.contributor.authorÇetin, H. Alperen
buir.contributor.authorDoğan, Emre
buir.contributor.authorTüzün, Eray
buir.contributor.orcidTüzün, Eray|0000-0002-5550-7816
dc.citation.epage21en_US
dc.citation.spage1en_US
dc.citation.volumeNumber208en_US
dc.contributor.authorÇetin, H. Alperen
dc.contributor.authorDoğan, Emre
dc.contributor.authorTüzün, Eray
dc.date.accessioned2022-02-24T11:53:10Z
dc.date.available2022-02-24T11:53:10Z
dc.date.issued2021-04-14
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractCode review is the process of inspecting code changes by a developer who is not involved in the development of the changeset. One of the initial and important steps of code review process is selecting code reviewer(s) for a given code change. To maximize the benefits of the code review process, the appropriate selection of the reviewer is essential. Code reviewer recommendation has been an active research area over the last few years, and many recommendation models have been proposed in the literature. In this study, we conduct a systematic literature review by inspecting 29 primary studies published from 2009 to 2020. Based on the outcomes of our review: (1) most preferred approaches are heuristic approaches closely followed by machine learning approaches, (2) the majority of the studies use open source projects to evaluate their models, (3) the majority of the studies prefer incremental training set validation techniques, (4) most studies suffer from reproducibility problems, (5) model generalizability and dataset integrity are the most common validity threats for the models and (6) refining models and conducting additional experiments are the most common future work discussions in the studies.en_US
dc.description.provenanceSubmitted by Esma Aytürk (esma.babayigit@bilkent.edu.tr) on 2022-02-24T11:53:10Z No. of bitstreams: 1 A_review_of_code_reviewer_recommendation_studies_Challenges_and_future_directions.pdf: 794762 bytes, checksum: 5b67b13886c1dbcf264d7b020d933a5f (MD5)en
dc.description.provenanceMade available in DSpace on 2022-02-24T11:53:10Z (GMT). No. of bitstreams: 1 A_review_of_code_reviewer_recommendation_studies_Challenges_and_future_directions.pdf: 794762 bytes, checksum: 5b67b13886c1dbcf264d7b020d933a5f (MD5) Previous issue date: 2021-04-14en
dc.embargo.release2023-04-14
dc.identifier.doi10.1016/j.scico.2021.102652en_US
dc.identifier.eissn1872-7964
dc.identifier.issn0167-6423
dc.identifier.urihttp://hdl.handle.net/11693/77607
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttps://doi.org/10.1016/j.scico.2021.102652en_US
dc.source.titleScience of Computer Programmingen_US
dc.subjectSystematic literature reviewen_US
dc.subjectCode reviewer recommendationen_US
dc.subjectReviewer recommendationen_US
dc.subjectModern code reviewen_US
dc.subjectPull requesten_US
dc.titleA review of code reviewer recommendation studies: Challenges and future directionsen_US
dc.typeReviewen_US

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