Invention Grant
- Patent Title: Software component defect prediction using classification models that generate hierarchical component classifications
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Application No.: US17929267Application Date: 2022-09-01
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Publication No.: US12061874B2Publication Date: 2024-08-13
- Inventor: Wei Zhang , Christopher Challis
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Kilpatrick Townsend & Stockton LLP
- The original application number of the division: US16259454 2019.01.28
- Main IPC: G06F40/284
- IPC: G06F40/284 ; G06F8/65 ; G06F8/70 ; G06F18/10 ; G06F18/214 ; G06F18/24 ; G06F40/44 ; G06N20/00

Abstract:
Systems and methods for facilitating updates to software programs via machine-learning techniques are disclosed. In an example, an application generates a feature vector from a textual description of a software defect by applying a topic model to the textual description. The application uses the feature vector and one or more machine-learning models configured to predict classifications and sub-classifications of the textual description. The application integrates the classifications and the sub-classifications into a final classification of the textual description that indicates a software component responsible for causing the software defect. The final classification is usable for correcting the software defect.
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