constrained random simulation

Concept

Constrained random simulation is a hardware verification approach in which input stimuli are generated randomly while satisfying declaratively specified input constraints, and the resulting stimuli are applied in simulation to validate design properties. The cited source emphasizes that effectiveness depends on both constraint-solver performance and the distribution of generated solutions, especially for mixed Boolean/integer variable domains.

First seen 7/17/2026

Last seen 7/17/2026

Evidence 1 chunks

Wiki v1

WIKI

Constrained random simulation

Constrained random simulation is a technique used in hardware verification in which input stimuli are generated randomly, subject to declaratively specified input constraints, and then applied in simulation to validate design properties.[1]

The cited source describes constrained random simulation as a main workhorse in hardware verification flows.[1] In this workflow, two factors are highlighted as especially important to overall efficiency:[1]

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RELATIONSHIPS

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Hardware Verification ← uses 1e

Constrained random simulation is a primary technique used in hardware verification flows.

input constraints uses → 1e

Constrained random simulation relies on input constraints to generate valid stimuli.

Stimulus Generation uses → 1e

Constrained random simulation depends on stimulus generation to produce test inputs.

LINKED ENTITIES

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Hardware Verification USES Extracted graph relationship

input constraints USES Extracted graph relationship

Stimulus Generation USES Extracted graph relationship

CITATIONS

5 sources

5 citations — click to expand

[1] Constrained random simulation generates input stimuli randomly while requiring them to satisfy declaratively specified input constraints, and applies those stimuli in simulation to validate design properties. Stimulus generation for constrained random simulation

[2] The cited source describes constrained random simulation as a main workhorse in hardware verification flows. Stimulus generation for constrained random simulation

[3] Overall efficiency depends critically on constraint-solver performance and on the distribution of generated solutions. Stimulus generation for constrained random simulation

[4] The discussed constraint-solving problem is for stimulus generation over mixed Boolean/integer variable domains. Stimulus generation for constrained random simulation

[5] The cited paper proposes a hybrid solver based on Markov-chain Monte Carlo methods with good performance and distribution. Stimulus generation for constrained random simulation