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Almost every non-trivial design contains at least one state machine, and exercising that state machine through its legal states, state transitions, and the different reasons for state transitions is key to verifying the design’s functionality. In some cases, we can exercise a state machine simply as a side-effect of performing normal operations on the design. In other cases, the state machine may be sufficiently complex that we must take explicit targeted steps to effectively exercise the state machine. In this article, we will see how inFact’s systematic stimulus generation and ability to generate constraint-aware functional coverage simplify the process of exercising a state machine by generating command sequences.
STATE MACHINE EXAMPLE
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