MalihehIzadi/IssueReportsManagement
Automatically managing Collectively-curated issue reports for maintenance and evolution goals of the software repositories, using state-of-the-art machine learning models.
Provides dual ML pipelines for automatic issue classification: objective detection (categorizing reports as bugs, enhancements, or support requests) and priority prediction for task assignment. The approach leverages state-of-the-art algorithms to analyze issue text and metadata, enabling data-driven triage without manual labeling. Includes both trained models and datasets supporting reproducible research on issue report analysis in software repositories.
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Jan 26, 2021
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