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Abstraction Refinement for Large Scale Model Checking

  • Book
  • © 2006

Overview

Authors:
  1. Chao Wang

    1. NEC Laboratories America, Princeton, USA

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    You can also search for this author in PubMed   Google Scholar

  2. Gary D. Hachtel

    1. Department of Electrical/Computer Engineering, University of Colorado, Boulder, USA

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    You can also search for this author in PubMed   Google Scholar

  3. Fabio Somenzi

    1. Department of Electrical/Computer Engineering, University of Colorado, Boulder, USA

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    You can also search for this author in PubMed   Google Scholar

  • Proposes fully automatic techniques for improving the performance of abstraction refinement
  • The algorithms in this book demonstrate significant improvement over prior techniques
  • Includes supplementary material: sn.pub/extras

Part of the book series: Integrated Circuits and Systems (ICIR)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction

    Pages 1-10

  3. Symbolic Model Checking

    Pages 11-40

  4. Abstraction

    Pages 41-54

  5. Refinement

    Pages 55-83

  6. Compositional SCC Analysis

    Pages 85-100

  7. Disjunctive Decomposition

    Pages 101-119

  8. Far Side Image Computation

    Pages 121-135

  9. Refining SAT Decision Ordering

    Pages 137-152

  10. Conclusions

    Pages 153-156

  11. Back Matter

    Pages 157-179
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Keywords

About this book

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.

Authors and Affiliations

  • NEC Laboratories America, Princeton, USA

    Chao Wang

  • Department of Electrical/Computer Engineering, University of Colorado, Boulder, USA

    Gary D. Hachtel, Fabio Somenzi

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