Coverage Learned Targeted Validation for Incremental HW Changes
Monica Farkash, Bryan Hickerson, Michael Behm · 2014
This paper addresses the challenges of minimizing the time and resources required to validate the changes between two Hardware (HW) model iterations of the same design. It introduces CLTV (Coverage Learned Targeted Validation), an automatic framework which learns during the verification process of the HW and uses the learned information to target the areas of the design that are affected by the incremental HW model iterations.