Invention Grant
- Patent Title: Detecting software build errors using machine learning
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Application No.: US16112506Application Date: 2018-08-24
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Publication No.: US10884893B2Publication Date: 2021-01-05
- Inventor: Alexander Sobran , Bo Zhang , Bradley C. Herrin
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Winstead PC
- Agent Robert A. Voigt, Jr.
- Main IPC: G06F11/36
- IPC: G06F11/36 ; G06N20/00

Abstract:
A method, system and computer program product for detecting software build errors. A classification system is created that identifies users' questions in crowdsource data pertaining to errors in computer programs that are associated with a log report. A model is built to classify log data as bug-related or not bug-related based on the classification system. Log reports from log data obtained from crowdsource data are identified as being bug-related based on the model. After vectorizing such log reports and storing the vectorized log reports, the language of a new build log report for a software product is vectorized upon completion of the build of the software product. If the vectorized log report is within a threshold amount of distance to a stored vectorized log report, then a copy of the log report (bug-related) and a source of the log report associated with the stored vectorized log report is provided.
Public/Granted literature
- US20200065220A1 DETECTING SOFTWARE BUILD ERRORS USING MACHINE LEARNING Public/Granted day:2020-02-27
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