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Coverage Directed Test Generation for Functional Verification Using Bayesian Networks (2003)
| Content Provider | CiteSeerX |
|---|---|
| Author | Ziv, Avi Fine, Shai |
| Description | In Proceedings of the 40th Design Automation Conference |
| Abstract | Functional verification is widely acknowledged as the bottleneck in the hardware design cycle. This paper addresses one of the main challenges of simulation based verification (or dynamic verification), by providing a new approach for Coverage Directed Test Generation (CDG). This approach is based on Bayesian networks and computer learning techniques. It provides an efficient way for closing a feedback loop from the coverage domain back to a generator that produces new stimuli to the tested design. In this paper, we show how to apply Bayesian networks to the CDG problem. Applying Bayesian networks to the CDG framework has been tested in several experiments, exhibiting encouraging results and indicating that the suggested approach can be used to achieve CDG goals. |
| File Format | |
| Publisher Date | 2003-01-01 |
| Access Restriction | Open |
| Subject Keyword | Feedback Loop Coverage Domain Cdg Framework Bayesian Network Cdg Goal Several Experiment Coverage Directed Test Generation Main Challenge Encouraging Result Functional Verification Using Bayesian Network Hardware Design Cycle Efficient Way Functional Verification Cdg Problem Test Generation New Stimulus Suggested Approach |
| Content Type | Text |
| Resource Type | Proceeding Conference Proceedings |
