An effective guidance strategy for abstraction-guided simulation

Abstract

Despite major advances in formal verification, simulation continues to be the dominant workhorse for functional verification. Abstraction-guided simulation has long been a promising framework for leveraging the power of formal techniques to help simulation reach difficult target states (assertion violations or coverage targets): model checking a smaller, abstracted version of the design avoids complexity blow-up, yet computes approximate distances from any state of the actual design to the target; these approximate distances are used during random simulation to guide the simulator. Unfortunately, the performance of previous work has been unreliable -sometimes great, sometimes poor.The problem is the guidance strategy. Because the abstract distances are approximate, a greedy strategy will get stuck in local optima. Previous works expanded the search horizon to try to avoid dead-ends. We explore such heuristics and find that they tend to perform poorly, adding too much search overhead for limited ability to escape dead-ends. Based on these experiments, we propose a new guidance strategy, which pursues a more global search and is better able to avoid getting stuck. Experiments show that our new guidance strategy is highly effective in most cases that are hard for random simulation and beyond the capacity of formal verification.

Efficient Testing of Concurrent Programs with Abstraction-Guided Symbolic Execution

“…Related works in hardware verification guide the simulation of the concrete model using an abstract model of boolean variables that represent the transition relation [14,15]; however, these works are limited to verifying circuit designs and boolean programs. The techniques cannot be extended to verify complex concurrent software systems.…”

Model validation for embedded systems using formal method-aided simulation

“…This assumption was formally expressed in Equation (1), but is repeated for convenience in Equation (12). Following the discussion above, a model capturing this assumption is generated and attached to the MUV.…”

“…Shyam et al [11] (with later elaboration by De Paula et al [12]) propose a technique where formal verification techniques are used to guide the simulation towards a certain verification goal, e.g. coverage.…”

Improved visibility in one-to-many trace concretization

“…The approaches of [7,14,8] use state distance in the abstract model as a metric to provide the necessary guidance for simulation. The authors of [14] advocate a simultaneous breadth and depth search of a concrete state space.…”

“…A "best" state-one deemed to have a better chance of reaching the "target" state-among all visited states is selected as the new starting point for the search. The authors of [7] argue that it is hard for a simulation trace to make progress and at the same time easy to lose ground. They advocate a technique where states visited during simulation are put in various buckets based on their abstract distance from the "target" state.…”