Year: 2023
Type: conference-paper
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 https://www.youtube.com/watch?v=ic2quUue7i8
Institution: Northern Arizona University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
Awards: CHS: Large: Collaborative Research: Gender-Inclusive Open Source through Gender-Inclusive Tools, CHS: SHF: Small: Collaborative Research: Scaffolding Skill Acquisition to Onboard Open Source Software Ecosystems, Scaffolding Computational Thinking in Introductory Computer Science through a Conversational Agent
OpenAlex ID: W4384026549