Invention Grant
- Patent Title: Bug categorization and team boundary inference via automated bug detection
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Application No.: US15469414Application Date: 2017-03-24
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Publication No.: US11288592B2Publication Date: 2022-03-29
- Inventor: Muiris Woulfe , Poornima Muthukumar , Yuanyuan Dong
- Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee Address: US WA Redmond
- Agency: Rainier Patents, P.S.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F11/36 ; G06N3/04

Abstract:
A machine learning model can be trained to infer the probability of the presence of categories of a software bug in a source code file. A bug tracker can provide information concerning the category to which a software bug belongs. The bug data supplied to a machine learning model for inferring the presence of particular categories of bugs can be filtered to exclude a specified category or categories of bugs. Information including but not limited to organizational boundaries can be inferred from the category of bugs present in a body of source code. The inferred organization boundaries can be used to generate team-specific machine learning models.
Public/Granted literature
- US20180276562A1 BUG CATEGORIZATION AND TEAM BOUNDARY INFERENCE VIA AUTOMATED BUG DETECTION Public/Granted day:2018-09-27
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