Hole analysis for functional coverage data

Abstract

One of the main goals of coverage tools is to provide the user with informative presentation of coverage information. Specifically, information on large, cohesive sets of uncovered tasks with common properties is very useful. This paper describes methods for discovering and reporting large uncovered spaces (holes) for cross-product functional coverage models. Hole analysis is a presentation method for coverage data that is both succinct and informative. Using case studies, we show how hole analysis was used to detect large uncovered spaces and improve the quality of verification.