Hybrid Intelligent Testing in Simulation-Based Verification
This addresses a domain-specific problem for hardware verification engineers, offering an incremental improvement by integrating existing methods.
The paper tackles the challenge of inefficient testing in simulation-based hardware verification, where millions of tests are often needed for coverage goals, by proposing a hybrid approach combining Coverage-Directed Test Selection and Novelty-Driven Verification to improve efficiency and effectiveness.
Efficient and effective testing for simulation-based hardware verification is challenging. Using constrained random test generation, several millions of tests may be required to achieve coverage goals. The vast majority of tests do not contribute to coverage progress, yet they consume verification resources. In this paper, we propose a hybrid intelligent testing approach combining two methods that have previously been treated separately, namely Coverage-Directed Test Selection and Novelty-Driven Verification. Coverage-Directed Test Selection learns from coverage feedback to bias testing toward the most effective tests. Novelty-Driven Verification learns to identify and simulate stimuli that differ from previous stimuli, thereby reducing the number of simulations and increasing testing efficiency. We discuss the strengths and limitations of each method, and we show how our approach addresses each method's limitations, leading to hardware testing that is both efficient and effective.