Improving Issue Trackers with AI-powered Analysis to Uncover Related Reports
May 22, 2025Microsoft Computer Science/Mathematics, 2024–25
Liaison(s): Topper Kain ’07, Henry Mbogu
Advisor(s): Melissa O’Neill
Students(s): Pearson Mewbourne (TL-S), Weston Crewe (TL-F), Mark Ying, Kishore Rajesh, Ian Li, Tejas Hegde
You have a bug. Surely you’re not the first one to encounter it! But today, finding similar bugs is too hard, and possible fixes get missed. The Clinic team addresses this problem for Microsoft engineers. When a user submits a bug report, the AI-powered bug characterization system identifies its core elements and finds the most similar bugs from a vast archive of other bug reports. That way, engineers are quickly connected with solutions, increasing their efficiency and productivity.