[2303.13418] GiveMeLabeledIssues: An Open Source Issue Recommendation System
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Computer Science > Software Engineering

arXiv:2303.13418 (cs)
[Submitted on 23 Mar 2023]

Title:GiveMeLabeledIssues: An Open Source Issue Recommendation System

Authors:Joseph Vargovich, Fabio Santos, Jacob Penney, Marco A. Gerosa, Igor Steinmacher
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Abstract:Developers often struggle to navigate an Open Source Software (OSS) project's issue-tracking system and find a suitable task. Proper issue labeling can aid task selection, but current tools are limited to classifying the issues according to their type (e.g., bug, question, good first issue, feature, etc.). In contrast, this paper presents a tool (GiveMeLabeledIssues) that mines project repositories and labels issues based on the skills required to solve them. We leverage the domain of the APIs involved in the solution (e.g., User Interface (UI), Test, Databases (DB), etc.) as a proxy for the required skills. GiveMeLabeledIssues facilitates matching developers' skills to tasks, reducing the burden on project maintainers. The tool obtained a precision of 83.9% when predicting the API domains involved in the issues. The replication package contains instructions on executing the tool and including new projects. A demo video is available at this https URL
Comments: MSR Data and Tool Showcase 2023
Subjects: Software Engineering (cs.SE); Machine Learning (cs.LG)
Cite as: arXiv:2303.13418 [cs.SE]
  (or arXiv:2303.13418v1 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2303.13418
Journal reference: IEEE/ACM 20th International Conference on Mining Software Repositories (MSR 2023), Data and Tool Showcase
Related DOI: https://doi.org/10.1109/MSR59073.2023.00061

Submission history

From: Fabio Marcos De Abreu Santos [view email]
[v1] Thu, 23 Mar 2023 16:39:31 UTC (11,357 KB)
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