Multi-language source code search engine
US11797281B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Aug 5, 2021 |
| Grant date | Oct 24, 2023 |
| Priority date | — |
| Expiry date | Mar 10, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0464
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning model is trained to translate source code from one or more programming languages into a common programming language. The machine learning model translates source code from the other languages into the common programming language. A language embedder generates a vector for each function in the source code, all of which is now in the common programming language. A user provides a text search query which is converted by a language embedder to a vector. Based on the vector of the text search query and the vectors for the source code, search results are generated and presented in a user interface. Additional machine learning models may be trained and used to measure function complexity, test coverage, documentation quantity and complexity, or any suitable combination thereof. These measures may be used to determine which search results to present, an order in which to present search results, or both.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.