Abstraction Refinement for Large Scale Model Checking
(Sprache: Englisch)
Abstraction Refinement for Large Scale Model Checking summarizes recent research on abstraction techniques for model checking large digital system. Considering both the size of today's digital systems and the capacity of state-of-the-art verification...
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Abstraction Refinement for Large Scale Model Checking summarizes recent research on abstraction techniques for model checking large digital system. Considering both the size of today's digital systems and the capacity of state-of-the-art verification algorithms, abstraction is the only viable solution for the successful application of model checking techniques to industrial-scale designs. This book describes recent research developments in automatic abstraction refinement techniques. The suite of algorithms presented in this book has demonstrated significant improvement over prior art; some of them have already been adopted by the EDA companies in their commercial/in-house verification tools.
Inhaltsverzeichnis zu „Abstraction Refinement for Large Scale Model Checking “
Symbolic Model Checking.- Abstraction.- Refinement.- Compositional SCC Analysis.- Disjunctive Decomposition.- Far Side Image Computation.- Refining SAT Decision Ordering.- Conclusions.
Autoren-Porträt von Chao Wang, Gary D. Hachtel, Fabio Somenzi
The techniques proposed in this book are fully automatic and are crucial at improving the performance of abstraction refinement. Their application to model checking can significantly increase the model checker's ability to handle large designs. Our experimental studies on some real-world benchmark circuits indicate that these automatic abstraction refinement techniques are the key to applying model checking to industrial-scale systems.
Bibliographische Angaben
- Autoren: Chao Wang , Gary D. Hachtel , Fabio Somenzi
- 2014, 2006, XIV, 179 Seiten, Maße: 21 x 23,3 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 1489993959
- ISBN-13: 9781489993953
Sprache:
Englisch
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