Bug categorization and team boundary inference via automated bug detection
US11288592B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 24, 2017 |
| Grant date | Mar 29, 2022 |
| Priority date | — |
| Expiry date | Apr 9, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning model can be trained to infer the probability of the presence of categories of a software bug in a source code file. A bug tracker can provide information concerning the category to which a software bug belongs. The bug data supplied to a machine learning model for inferring the presence of particular categories of bugs can be filtered to exclude a specified category or categories of bugs. Information including but not limited to organizational boundaries can be inferred from the category of bugs present in a body of source code. The inferred organization boundaries can be used to generate team-specific machine learning models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.