Functional Verification Coverage Measurement and Analysis

As the complexity of today’s ASIC and SoC designs continues to

increase, the challenge of verifying these designs intensifies at an even

greater rate. Advances in this discipline have resulted in many sophisticated

tools and approaches that aid engineers in verifying complex designs. However,

the age-old question of when is the verification job done, remains one of

the most difficult questions to answer. And, the process of measuring verification

progress is poorly understood.

For example, consider automatic random stimulus generators, modelbased

test generators, or even general-purpose constraint solvers used by

high-level verification languages (such as e). At issue is knowing which portions

of a design are repeatedly exercised from the generated stimulus — and

which portions of the design are not touched at all. Or, more fundamentally,

exactly what functionality has been exercised using these techniques. Historically,

answering these questions (particularly for automatically generated

stimulus) has been problematic. This challenge has led to the development

of various coverage metrics to aid in measuring progress, ranging from code

coverage (used to identify unexercised lines of code) to contemporary functional

coverage (used to identify unexercised functionality). Yet, even with

the development of various forms of coverage and new tools that support

coverage measurement, the use of these metrics within the verification flow

tends to be ad-hoc, which is predominately due to the lack of well-defined,

coverage-driven verification methodologies.

Prior to introducing a coverage-driven verification methodology, Functional

Verification Coverage Measurement and Analysis establishes a sound

foundation for its readers by reviewing an excellent and comprehensive list of

terms that is common to the language of coverage. Building on this knowledge,

the author details various forms of measuring progress that have historically

been applicable to a traditional verification flow, as well as new forms

applicable to a contemporary verification flow.

Functional Verification Coverage Measurement and Analysis is the first

book to introduce a useful taxonomy for coverage metric classification.

Using this taxonomy, the reader clearly understands the process of creating

an effective coverage model. Ultimately, this book presents a coveragedriven

verification methodology that integrates multiple forms of coverage

and strategies to help answer the question when is the verification job done.

Andrew Piziali has created a wonderfully comprehensive textbook on

the language, principles, and methods pertaining to the important area of

Functional Verification Coverage Measurement and Analysis. This book

should be a key reference in every engineer’s library.

Harry Foster

Chief Methodologist

Jasper Design Automation, Inc.

x Functional Verification Coverage Measurement and Analysis