Diversifying stimulus generation in constrained random simulation by learning distribution history

An apparatus, comprising:

• a processor;
• and
• a non-transitory computer-readable storage medium storing instructions that, when executed by the processor, cause the apparatus to perform a method for generating constrained random stimuli during functional verification of a design under verification (DUV), the method comprising:
• computing an observed probability distribution for each variable in a set of variables based on at least a first random solution generated using a set of constraints that is defined over the set of variables;
• computing a correction probability distribution for each variable in the set of variables based on the observed probability distribution and an intended probability distribution;
• and
• while generating at least a second random solution using the set of constraints, selecting a random value for a given variable in the set of variables based on the correction probability distribution for the given variable.

A method for generating constrained random stimuli during functional verification of a design under verification (DUV), the method comprising:

• computing, by using a processor, an observed probability distribution for each variable in a set of variables based on at least a first random solution generated using a set of constraints that is defined over the set of variables;
• computing a correction probability distribution for each variable in the set of variables based on the observed probability distribution and an intended probability distribution;
• while generating at least a second random solution using the set of constraints, selecting a random value for a given variable in the set of variables based on the correction probability distribution for the given variable;
• and
• wherein the observed probability distribution is continuously updated and stored as the constrained random stimuli are generated.