Constrained random stimuli generation

Constrained Random Stimuli Generation

Technique

Constrained random stimuli generation is a functional verification technique that produces randomized test inputs subject to user-defined constraints, enabling efficient exploration of a design's input space without exhaustive handcrafted stimulus authoring.

First seen 9/27/2026

Last seen 9/27/2026

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WIKI

Overview

Constrained random stimuli generation is a technique used in functional verification, particularly in hardware and SystemC design flows. Rather than relying solely on static, hand-authored test vectors, the technique automatically generates randomized stimuli that satisfy a set of declaratively specified constraints. This approach is widely used to drive simulation-based regressions, where the goal is to efficiently reach coverage targets across a design under test (DUT).

Motivation

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RELATIONSHIPS

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CRAVE ← implements 98% 1e

The project describes CRAVE as a library specifically for constrained random stimuli generation, indicating it implements this technique.

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CRAVE IMPLEMENTS Extracted graph relationship

CITATIONS

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5 citations — click to expand

[1] Constrained random stimuli generation depends on manually crafted distributions that are difficult to design and often ineffective. NOVA: Coordinated Test Selection and Bayes-Optimized Constrained Randomization for Accelerated Coverage Closure

[2] Bayes-optimized constrained randomization combined with coverage-aware test selection can achieve up to a 2.82× coverage convergence speedup on multiple RTL designs without human-crafted heuristics. NOVA: Coordinated Test Selection and Bayes-Optimized Constrained Randomization for Accelerated Coverage Closure

[3] CRAVE is a library for constrained random stimuli generation whose syntax fits naturally with C++ and SystemC. CRAVE — Institute for Computer Systems, JKU

[4] CRAVE supports dynamic constraints, dynamic data structures (including STL vectors), inline and incrementally updatable constraints, and uses a portfolio of BDD-based and SAT/SMT-based solvers for fast constraint solving. CRAVE — Institute for Computer Systems, JKU

[5] CRAVE was contributed to the Accellera Systems Initiative and is maintained by its Verification Working Group. CRAVE — Institute for Computer Systems, JKU