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IEEE Transactions on Computers
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DAC '91 Proceedings of the 28th ACM/IEEE Design Automation Conference
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ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
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ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
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Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
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ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
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ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Adaptive variable reordering for symbolic model checking
Proceedings of the 1998 IEEE/ACM international conference on Computer-aided design
FMCAD '96 Proceedings of the First International Conference on Formal Methods in Computer-Aided Design
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FMCAD '98 Proceedings of the Second International Conference on Formal Methods in Computer-Aided Design
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CSD '98 Proceedings of the 1998 International Conference on Application of Concurrency to System Design
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ICCD '97 Proceedings of the 1997 International Conference on Computer Design (ICCD '97)
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Proceedings of the 2001 Asia and South Pacific Design Automation Conference
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Proceedings of the 2001 Asia and South Pacific Design Automation Conference
Ordered binary decision diagrams
Logic Synthesis and Verification
Data structures for Boolean functions
Computational Discrete Mathematics
WWW.BDD-Portal.ORG: an experimentation platform for binary decision diagram algorithms
Experimental algorithmics
Decomposing image computation for symbolic reachability analysis using control flow information
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
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This paper proposes lazy group sifting for dynamic variable re-ordering during state traversal. The proposed method relaxes the idea of pairwise grouping of present state variables and their corresponding next state variables. This is done to produce better variable orderings during image computation without causing BDD size blowup in the substitution of next state variables with present state variables at the end of image computation. Experimental results show that our approach is more robust in state traversal than the approaches that either unconditionally group variable pairs or never group them.