Name
Abstract | ||
|---|---|---|
Coverage analysis is used to monitor the quality of the verification process. Reports provided by coverage tools help users identify areas in the design that have not been adequately tested. Because of their sheer size, the analysis of large coverage models can be an intimidating and time-consuming task. Practically, it can only be done by focusing on specific parts of the model. This paper presents a method for defining views onto the coverage data of cross-product functional coverage models. The proposed method allows users to focus on certain aspects of the coverage data to extract relevant, useful information, thereby improving the quality of the coverage analysis. A number of examples are provided that show how the proposed method improved the verification of actual designs. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1145/996566.996579 | DAC |
Keywords | Field | DocType |
large coverage model,cross-product functional coverage model,coverage tool,defining view,coverage view,certain aspect,verification process,coverage data,coverage analysis,functional coverage analysis,actual design,data analysis,logic design,data mining,hardware,system testing,functional verification | Code coverage,Logic synthesis,Data mining,Permission,Functional verification,System testing,Computer science,Coverage data | Conference |
ISSN | ISBN | Citations |
0738-100X | 1-58113-828-8 | 8 |
PageRank | References | Authors |
0.66 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sigal Asaf | 1 | 14 | 1.49 |
| eitan marcus | 2 | 166 | 11.76 |
| Avi Ziv | 3 | 465 | 72.49 |