Invention Grant
- Patent Title: Utilizing machine learning models for automated software code modification
-
Application No.: US17164355Application Date: 2021-02-01
-
Publication No.: US11455161B2Publication Date: 2022-09-27
- Inventor: Rajendra Tanniru Prasad , Aditi Kulkarni , Koushik M. Vijayaraghavan , Priya Athreyee , Pradeep Senapati , Kamakshi Girish , Dibyendu Chattopadhyay , Nivedita Shah
- Applicant: Accenture Global Solutions Limited
- Applicant Address: IE Dublin
- Assignee: Accenture Global Solutions Limited
- Current Assignee: Accenture Global Solutions Limited
- Current Assignee Address: IE Dublin
- Agency: Harrity & Harrity, LLP
- Main IPC: G06F8/65
- IPC: G06F8/65 ; G06F8/71 ; G06N20/00 ; G06F11/36 ; G06K9/62

Abstract:
A device may receive requirement data identifying a requirement for modification of software code, and may process the requirement data, with a machine learning model, to identify entities and intents in the software code and to generate a query. The device may process the query, with a code locator model, to encode text of the query into high-dimensional vectors and to identify a semantic similarity between the high-dimensional vectors and code text. The device may process the query, the semantic similarity, and the code text, with a code developer model, to generate metadata, and may utilize the metadata to identify an identifier associated with the software code. The device may determine, utilizing the identifier, a portion of the software code, and may modify the portion of the software code based on the query to generate modified software code. The device may perform actions based on the modified software code.
Public/Granted literature
- US20220244937A1 UTILIZING MACHINE LEARNING MODELS FOR AUTOMATED SOFTWARE CODE MODIFICATION Public/Granted day:2022-08-04
Information query