Auto-tuning program analysis tools using machine learning
US10135856B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jan 25, 2016 |
| Grant date | Nov 20, 2018 |
| Priority date | — |
| Expiry date | Jan 25, 2036 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1483
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Machine learning (ML) significantly reduces false alarms generated by an automated analysis tool performing static security analysis. Using either user-supplied or system-generated annotation of particular findings, a “hypothesis” is generated about how to classify other static analysis findings. The hypothesis is implemented as a machine learning classifier. To generate the classifier, a set of features are abstracted from a typical witness, and the system compares feature sets against one another to determine a set of weights for the classifier. The initial hypothesis is then validated against a second set of findings, and the classifier is adjusted as necessary based on how close it fits the new data. Once the approach converges on a final classifier, it is used to filter remaining findings in the report.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.