Harnessing machine learning to improve the success rate of stimuli generation
US7331007B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 7, 2005 |
| Grant date | Feb 12, 2008 |
| Priority date | — |
| Expiry date | May 1, 2026 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01R31/318357
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Test generation is improved by learning the relationship between an initial state vector for a stimuli generator and generation success. A stimuli generator for a design-under-verification is provided with information about the success probabilities of potential assignments to an initial state bit vector. Selection of initial states according to the success probabilities ensures a higher success rate than would be achieved without this knowledge. The approach for obtaining an initial state bit vector employs a CSP solver. A learning system is directed to model the behavior of possible initial state assignments. The learning system develops the structure and parameters of a Bayesian network that describes the relation between the initial state and generation success.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.