Automatic Constraint Generation
ConceptAutomatic constraint generation is a research direction within constraint-based stimuli generation for simulation-based functional verification. It aims to derive simulation constraints automatically—rather than through manual composition—to support coverage-driven verification of complex Systems-on-Chips (SoCs). The technique was introduced for guided random simulation by Yeh and Huang (2010) and has been pursued by follow-up work that improves the controllability of internal signals and reduces the manual effort required to formulate stimuli constraints.
WIKI
Automatic Constraint Generation
Definition and Motivation
Automatic constraint generation refers to techniques that derive simulation constraints algorithmically, instead of relying on a verification engineer to hand-write them. It is positioned within the broader area of constraint-based stimuli generation, which is widely used in simulation-based verification of complex Systems-on-Chips (SoCs) to produce stimuli that deliberately trigger corner-case behavior and previously under-covered scenarios. The motivation for automating constraint generation is twofold: it reduces the time-consuming and error-prone manual constraint composition process, and it can improve the controllability of internal signals, both of which contribute to higher functional coverage during simulation-based verification.
NEIGHBORHOOD
No graph connections found for this entity yet. It may appear in future ingestion runs.
explore full graph →