Code coverage metrics, adapted from the software industry, provide a structural coverage view of design verification. Structure refers to components of the design such as lines of code, variables, and ...

Simple code-coverage metrics such as line, branch and sub-expression coverage have been used for many years. These metrics simply identify areas of the RTL code that have not been exercised at all in ...

Christian Gruber takes some time to clarify the TDD stance on using code coverage metrics. He discusses what code coverage metrics do and don't tell you, how TDD fits into the picture, and how one ...

Code coverage metrics provide insight into the degree to which source code is executed during a test—that is, which lines of code have or have not been executed, and what percentage of an ...

Code coverage metrics must be used in conjunction with other metrics such as functional coverage, assertion coverage, and formal equivalence checkers [1] to measure verification completion.

This example shows how to generate coverage for unit and integration tests using Maven and Sonar. It uses very simple techniques and should only take 10-15 minutes to get running in any existing ...

Use of industry standard coverage metrics and its relevance to the chip test plan are discussed. Specific examples of coverage and its limitations are also mentioned.

Achieving 80 percent code coverage in testing suites is a reasonable goal and QA coverage metrics should only be presented with complementary metrics to provide appropriate context.