Evaluating an assistant for creating bug report assignment recommenders

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dc.contributor.authorAnvik, John
dc.date.accessioned2019-04-01T02:41:21Z
dc.date.available2019-04-01T02:41:21Z
dc.date.issued2016
dc.description.abstractSoftware development projects receive many change requests each day and each report must be examined to decide how the request will be handled by the project. One decision that is frequently made is to which software developer to assign the change request. Efforts have been made toward semi automating this decision,with most approaches using machine learning algorithms. However, using machine learning to create an assignment recommender is a complex process that must be tailored to each individual software development project. The Creation Assistant for Easy Assignment (CASEA) tool leverages a project member’s knowledge for creating an assignment recommender. This paper presents the results of a user study using CASEA. The user study shows that users with limited project knowledge can quickly create accurate bug report assignment recommenders.en_US
dc.description.peer-reviewYesen_US
dc.identifier.citationAnvik, J. (2016). Evaluating an assistant for creating bug report assignment recommenders. Workshop on Engineering Computer-Human Interaction in Recommender Systems (EnCHIReS), Brussels, Belgium, 21-24 June, 2016, pp. 26-39.en_US
dc.identifier.urihttps://hdl.handle.net/10133/5311
dc.language.isoen_USen_US
dc.publisher.departmentDepartment of Mathematics & Computer Scienceen_US
dc.publisher.facultyArts and Scienceen_US
dc.publisher.institutionUniversity of Lethbridgeen_US
dc.subjectBug report triageen_US
dc.subjectAssignment recommendationen_US
dc.subjectMachine learningen_US
dc.subjectRecommender creationen_US
dc.subjectComputer supported worken_US
dc.titleEvaluating an assistant for creating bug report assignment recommendersen_US
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