TY - GEN
T1 - GiveMeLabeledIssues
T2 - 20th IEEE/ACM International Conference on Mining Software Repositories, MSR 2023
AU - Vargovich, Joseph
AU - Santos, Fabio
AU - Penney, Jacob
AU - Gerosa, Marco A.
AU - Steinmacher, Igor
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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 https://www.youtube.com/watch?v=ic2quUue7i8
AB - 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 https://www.youtube.com/watch?v=ic2quUue7i8
KW - Issue Tracker
KW - Label
KW - Machine Learning
KW - Open Source Software
KW - Tag
KW - Task
UR - http://www.scopus.com/inward/record.url?scp=85166295936&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85166295936&partnerID=8YFLogxK
U2 - 10.1109/MSR59073.2023.00061
DO - 10.1109/MSR59073.2023.00061
M3 - Conference contribution
AN - SCOPUS:85166295936
T3 - Proceedings - 2023 IEEE/ACM 20th International Conference on Mining Software Repositories, MSR 2023
SP - 402
EP - 406
BT - Proceedings - 2023 IEEE/ACM 20th International Conference on Mining Software Repositories, MSR 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 15 May 2023 through 16 May 2023
ER -