Unified coverage driven mechanism for speeding up verification convergence

Functional coverage helps to examine test scenarios, by providing metrics that give information about the test case or design-under-test (DUT) reached states. System Verilog language provides dedicated syntax to make it possible, such as cover group and cover point objects. Under cover group we have cover points and cross points, again under them we have cover bins and cross bins respectively. However using cover points we can directly ensure certain values/set of values of the signals and using the cross points we can cover a crossing between two or more individual bins, where we can directly ensure the piece of the scenario only. But using these cover points and cross points we cannot directly and clearly ensure whether an end to end scenario (qualified data traversing from initial state to final state with in stipulated clock cycles) has been exercised by the stimulus. To achieve that here we are proposing the “scenario cover points” which can directly in a single shot, will ensure end to end scenario exercised in the simulation. The constrained random simulation (CRS) is widely used during the pre-silicon verification to cover width and depth of the design. But improving functional coverage efficiently in a verification environment based on CRS could be time consuming, since we need to run verification tests multiple times by increasing the seed number until we cover everything (all corner states of the design). On the other hand manually crafting direct test patterns completely is not practical since we have exhaustive state space to verify. So here we are proposing the method “blend of focused and constrained random stimulus with scenario bins on top of usual bins (bins under cover points and cross points)” to exercise the primary end to end scenarios quickly and to cover the width and depth of the design. To the best of our knowledge, in the domain of pre-silicon functional verification this is the first work which proposes on blend of focused and constrained random stimulus with scenario bins on top of usual bins.