Suggesting reviewers of software artifacts using traceability graphs

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buir.contributor.authorSülün, Emre
dc.citation.epage1252en_US
dc.citation.spage1250en_US
dc.contributor.authorSülün, Emreen_US
dc.contributor.editorApel, S.
dc.contributor.editorDumas, M.
dc.contributor.editorRusso, A.
dc.contributor.editorPfahl, D.
dc.coverage.spatialTallin, Estoniaen_US
dc.date.accessioned2020-01-30T08:00:39Z
dc.date.available2020-01-30T08:00:39Z
dc.date.issued2019
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 26-30 August 2019en_US
dc.descriptionConference Name: 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2019en_US
dc.description.abstractDuring the lifecycle of a software project, software artifacts constantly change. A change should be peer-reviewed to ensure the software quality. To maximize the benefit of review, the reviewer(s) should be chosen appropriately. However, choosing the right reviewer(s) might not be trivial especially in large projects. Researchers developed different methods to recommend reviewers. In this study, we introduce a novel approach for reviewer recommendation problem. Our approach utilizes the traceability graph of a software project and assigns a know-about score to each developer, then recommends the developers who have the maximum know-about score for an artifact. We tested our approach on an open source project and achieved top-3 recall of 0.85 with an MRR (mean reciprocal ranking) of 0.73.en_US
dc.description.provenanceSubmitted by Zeynep Aykut (zeynepay@bilkent.edu.tr) on 2020-01-30T08:00:39Z No. of bitstreams: 1 Suggesting_reviewers_of_software_artifacts_using_traceability_graphs.pdf: 591910 bytes, checksum: 07ed9c5b649c70ce500c6e8c713c26c8 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-01-30T08:00:39Z (GMT). No. of bitstreams: 1 Suggesting_reviewers_of_software_artifacts_using_traceability_graphs.pdf: 591910 bytes, checksum: 07ed9c5b649c70ce500c6e8c713c26c8 (MD5) Previous issue date: 2019en
dc.description.sponsorshipACM SIGSOFTen_US
dc.identifier.doi10.1145/3338906.3342507en_US
dc.identifier.isbn9781450355728
dc.identifier.urihttp://hdl.handle.net/11693/52920
dc.language.isoEnglishen_US
dc.publisherAssociation for Computing Machinery, Incen_US
dc.relation.isversionofhttps://dx.doi.org/10.1145/3338906.3342507en_US
dc.source.titleProceedings of the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2019en_US
dc.subjectReviewer recommendationen_US
dc.subjectCode reviewen_US
dc.subjectSoftware traceabilityen_US
dc.titleSuggesting reviewers of software artifacts using traceability graphsen_US
dc.typeConference Paperen_US

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