Stimulus generation for constrained random simulation
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Automatic constraint generation for guided random simulation
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
Proceedings of the International Conference on Computer-Aided Design
A robust general constrained random pattern generator for constraints with variable ordering
Proceedings of the International Conference on Computer-Aided Design
Proceedings of the 50th Annual Design Automation Conference
A scalable and nearly uniform generator of SAT witnesses
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
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Simulation by random vectors is meaningful only if the vectors meet certain requirements on the environment that drives the design under verification. When that environment is modeled by constraints, we face the problem of solving constraints efficiently. We present an efficient algorithm for simplifying conjunctive Boolean constraints defined over state and input variables, and apply it to constrained random simulation vector generation using binary decision diagrams (BDDs). The method works by extracting "hold-constraints" from the system of constraints. Hold-constraints are deterministic and trivially resolvable. They can be used to simplify the original constraints as well as refine the conjunctive partition. Experiments demonstrate significant reductions in the time and space required for constructing the conjunction BDDs, and the time spent in vector generation during simulation.