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dc.contributor.author Anvik, John
dc.date.accessioned 2019-04-01T02:41:21Z
dc.date.available 2019-04-01T02:41:21Z
dc.date.issued 2016
dc.identifier.citation Anvik, 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.uri https://hdl.handle.net/10133/5311
dc.description.abstract Software 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 semiautomatingthisdecision,withmostapproachesusingmachine learning algorithms. However, using machine learning to createanassignmentrecommenderisacomplexprocessthatmust 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.language.iso en_US en_US
dc.subject Bug report triage en_US
dc.subject Assignment recommendation en_US
dc.subject Machine learning en_US
dc.subject Recommender creation en_US
dc.subject Computer supported work en_US
dc.title Evaluating an assistant for creating bug report assignment recommenders en_US
dc.publisher.faculty Arts and Science en_US
dc.publisher.department Department of Mathematics & Computer Science en_US
dc.description.peer-review Yes en_US
dc.publisher.institution University of Lethbridge en_US


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