Abstraction-Guided Simulation Using Markov Analysis for Functional Verification

Abstract
This paper presents a novel abstraction-guided simulation approach for functional verification. The results of Markov analysis of the abstract model of the design under verification are used as the guidance of simulation on the concrete design. The results of the Markov analysis can offer the information about how hard it is to reach each abstract state from the initial state, and how hard it is to reach certain target states from each abstract state. Such information is able to guide the simulation in two aspects: 1) in exploring abstract state space and 2) in exercising target state. Assuming a good abstract model, experimental results show that the simulation using Markov analysis as guidance is highly efficient in both aspects.
Funding Information
  • National Natural Science Foundation of China (61432017, 61176040, 61221062)
  • National Basic Research Program of China (973) (2011CB302501)

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