Invention Grant
- Patent Title: Code change graph node matching with machine learning
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Application No.: US16946982Application Date: 2020-07-14
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Publication No.: US11340873B2Publication Date: 2022-05-24
- Inventor: Catalina Codruta Cangea , Qianyu Zhang
- Applicant: X Development LLC
- Applicant Address: US CA Mountain View
- Assignee: X Development LLC
- Current Assignee: X Development LLC
- Current Assignee Address: US CA Mountain View
- Agency: Middleton Reutlinger
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F8/33 ; G06N5/04

Abstract:
Implementations are described herein for training and using machine learning to determine mappings between matching nodes of graphs representing predecessor source code snippets and graphs representing successor source code snippets. In various implementations, first and second graphs may be obtained, wherein the first graph represents a predecessor source code snippet and the second graph represents a successor source code snippet. The first graph and the second graph may be applied as inputs across a trained machine learning model to generate node similarity measures between individual nodes of the first graph and nodes of the second graph. Based on the node similarity measures, a mapping may be determined across the first and second graphs between pairs of matching nodes.
Public/Granted literature
- US20220019410A1 CODE CHANGE GRAPH NODE MATCHING WITH MACHINE LEARNING Public/Granted day:2022-01-20
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