Automatic test program generation for pipelined processors
ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
Micro architecture coverage directed generation of test programs
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
High-level test generation for design verification of pipelined microprocessors
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
PROTEST: a tool for probabilistic testability analysis
DAC '85 Proceedings of the 22nd ACM/IEEE Design Automation Conference
Model checking
IEEE Design & Test
Modeling Fault Coverage of Random Test Patterns
Journal of Electronic Testing: Theory and Applications
Coverage directed test generation for functional verification using bayesian networks
Proceedings of the 40th annual Design Automation Conference
Test generation costs analysis and projections
DAC '80 Proceedings of the 17th Design Automation Conference
Constraint Processing
FPgen - a test generation framework for datapath floating-point verification
HLDVT '03 Proceedings of the Eighth IEEE International Workshop on High-Level Design Validation and Test Workshop
Comprehensive Functional Verification: The Complete Industry Cycle (Systems on Silicon)
Comprehensive Functional Verification: The Complete Industry Cycle (Systems on Silicon)
Functional Verification Coverage Measurement and Analysis
Functional Verification Coverage Measurement and Analysis
A new algorithm for sampling CSP solutions uniformly at random
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Microprocessor Verification via Feedback-Adjusted Markov Models
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Coverage is an important measure for the quality and completeness of the functional verification of hardware logic designs. Verification teams spend a significant amount of time looking for bugs in the design and in providing high-quality coverage. This process is performed through the use of various sampling strategies for selecting test inputs. The selection of sampling strategies to achieve the verification goals is typically carried out in an intuitive manner. We studied several commonly used sampling strategies and provide a probabilistic framework for assessing and comparing their relative values. For this analysis, we derived results for two measures of interest: first, the probability of finding a bug within a given number of samplings; and second, the expected number of samplings until a bug is detected. These results are given for both recurring sampling schemes, in which the same inputs might be selected repeatedly, and for nonrecurring sampling schemes, in which already sampled inputs are never selected again. By considering results from the theory of search, and more specifically, from the well-known multiarmed bandit problem, we demonstrate the optimality of a greedy sampling strategy within our defined framework.