1999 IEEE/ACM International Conference on Computer-Aided Design. Digest of Technical Papers (Cat. No.99CH37051)
DOI: 10.1109/iccad.1999.810715
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Modeling design constraints and biasing in simulation using BDDs

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Cited by 68 publications
(50 citation statements)
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“…To improve coverage of the Verilog simulation, a dynamically biased random simulation test bench [19] can also be written directly in ESL scripts.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…To improve coverage of the Verilog simulation, a dynamically biased random simulation test bench [19] can also be written directly in ESL scripts.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…Clarke et al further researched the problem of specifications and generators in [20]. However, BDDs were used to demonstrate a practical approach to this problem in the SimGen project [21]. Later on, Shimizu et al [22] [23] automated this approach to verify large industrial designs.…”
Section: Previous Workmentioning
confidence: 99%
“…Our construction technique is most closely related to the stimulus generation algorithm of Yuan et al [19] and the parametric constraint representation of Aagaard et al [1]. Yuan et al present an algorithm which generates random stimuli satisfying a constraint, represented as a BDD, which may depend on state variables of the design.…”
Section: Related Workmentioning
confidence: 99%
“…While the circuit we construct does not reduce the number of input variables compared to the unconstrained circuit, the constraints on the inputs can prevent false error reports that could have occurred if improper input stimuli were allowed to propagate into the module [19]. The constraints may also improve the efficiency of state exploration techniques such as symbolic simulation by reducing BDD sizes [1].…”
Section: Introductionmentioning
confidence: 99%
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