Open Source Software projects add labels to open issues to help contributors choose tasks . Current automatic approaches for creating labels are mostly limited to classifying issues as a bug/non-bug . We leverage the issues’ description and the project history to build prediction models, which resulted in precision up to82% and recall up to 97.8% . We also ran a user study to assess theselabels’ relevancy to potential contributors . The results show that the labels were useful to participants in choosing tasks, and the API-domain labels wereselected more often than the existing architecture-based labels . Our resultscan inspire the creation of tools to automatically label issues, helpingdevelopers to find tasks that better match their skills

Author(s) : Fabio Santos, Igor Wiese, Bianca Trinkenreich, Igor Steinmacher, Anita Sarma, Marco Gerosa

Links : PDF - Abstract

Code :
Coursera

Keywords : labels - issues - tasks - bug - open -

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