[Submitted on 19 May 2022 (

v1

), last revised 16 Oct 2022 (this version, v3)]

Title:Hybrid Intelligent Testing in Simulation-Based Verification

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Abstract: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.

Submission history

From: Nyasha Masamba [

view email

]

[v1]

Thu, 19 May 2022 13:22:08 UTC (358 KB)

[v2]

Wed, 22 Jun 2022 16:59:13 UTC (359 KB)

[v3]

Sun, 16 Oct 2022 16:21:40 UTC (359 KB)