Evaluating an assistant for creating bug report assignment recommenders

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Date
2016
Authors
Anvik, John
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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 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.
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Keywords
Bug report triage , Assignment recommendation , Machine learning , Recommender creation , Computer supported work
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.
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