Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Elements of information theory
Elements of information theory
Functional verification methodology for microprocessors using the Genesys test-program generator
DATE '99 Proceedings of the conference on Design, automation and test in Europe
ACM Computing Surveys (CSUR)
Writing testbenches: functional verification of HDL models
Writing testbenches: functional verification of HDL models
High quality behavioral verification using statistical stopping criteria
Proceedings of the conference on Design, automation and test in Europe
Hole analysis for functional coverage data
Proceedings of the 39th annual Design Automation Conference
Coverage directed test generation for functional verification using bayesian networks
Proceedings of the 40th annual Design Automation Conference
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Advanced Analysis Techniques for Cross-Product Coverage
IEEE Transactions on Computers
Automatic Boosting of Cross-Product Coverage Using Bayesian Networks
HVC '08 Proceedings of the 4th International Haifa Verification Conference on Hardware and Software: Verification and Testing
Coverage-Directed Test Generation Automated by Machine Learning -- A Review
ACM Transactions on Design Automation of Electronic Systems (TODAES)
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Coverage directed test generation (CDG) is a technique for providing feedback from the coverage domain back to a generator that produces new stimuli to the tested design. In this paper, we describe two algorithms that act in a CDG framework. The first algorithm controls the coverage events distribution using a "water-filling" approach. The second algorithm improves the efficiency of the covering process using clustering techniques.