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Dynamic abstraction using SAT-based BMC
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 42nd annual Design Automation Conference table of contents
Anaheim, California, USA
SESSION: SAT: cool algorithms and hot applications table of contents
Pages: 754 - 757  
Year of Publication: 2005
ISBN:1-59593-058-2
Authors
Liang Zhang  Cadence Design Systems, San Jose, CA
Mukul R. Prasad  Fujitsu Laboratories of America, Sunnyvale, CA
Michael S. Hsiao  Virginia Tech, Blacksburg, VA
Thomas Sidle  Fujitsu Laboratories of America, Sunnyvale, CA
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

We propose a new dynamic method of abstraction, which can be applied during successive steps of the model checking algorithm to further reduce the model produced by traditional static abstraction methods. This is facilitated by information gathered from an analysis of the proof of unsatisfiability of SAT-based bounded model checking problems formulated on the original design. The dynamic abstraction effectively allows the model checker to work with smaller abstract models. Experiments on several industrial benchmarks demonstrate that dynamic abstraction can significantly improve both the performance and the capacity of typical abstraction refinement flows.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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M. Glusman et al. Multiple-Counterexample Guided Iterative Abstraction Refinement: An Industrial Evaluation. In Tools and Algorithms for the Construction and Analysis of Systems, pages 176--191, April 2003.
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K. L. McMillan and N. Amla. Automatic abstraction without counterexamples. In Tools and Algorithms for the Construction and Analysis of Systems, LNCS 2619, pages 2--17, April 2003.
 
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Collaborative Colleagues:
Liang Zhang: colleagues
Mukul R. Prasad: colleagues
Michael S. Hsiao: colleagues
Thomas Sidle: colleagues