Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Finding the optimal variable ordering for binary decision diagrams
DAC '87 Proceedings of the 24th ACM/IEEE Design Automation Conference
Finding the Optimal Variable Ordering for Binary Decision Diagrams
IEEE Transactions on Computers
Reduction of OBDDs in linear time
Information Processing Letters
Symmetry detection and dynamic variable ordering of decision diagrams
ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
Who are the variables in your neighborhood
ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
Improving the Variable Ordering of OBDDs Is NP-Complete
IEEE Transactions on Computers
Dynamic variable ordering for ordered binary decision diagrams
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Fast exact minimization of BDDs
DAC '98 Proceedings of the 35th annual Design Automation Conference
On the Complexity of Constructing Optimal Ordered Binary Decision Diagrams
MFCS '94 Proceedings of the 19th International Symposium on Mathematical Foundations of Computer Science 1994
The Complexity of the Optimal Variable Ordering Problems of Shared Binary Decision Diagrams
ISAAC '93 Proceedings of the 4th International Symposium on Algorithms and Computation
Global rebuilding of OBDDs Avoiding Memory Requirement Maxima
Proceedings of the 7th International Conference on Computer Aided Verification
Speeding up variable reordering of OBDDs
ICCD '97 Proceedings of the 1997 International Conference on Computer Design (ICCD '97)
Ordered binary decision diagrams
Logic Synthesis and Verification
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The exact minimization of the size of Ordered Binary Decision Diagrams (OBDD) is known to be an NP-complete problem. The available heuristical solutions of the problem still do not satisfy requirements of the practical applications. Development of the efficient algorithms that find acceptable variable orders within a short time and with a modest memory overhead is hence higly desired. In this paper we contribute to the solution of the minimization problem by a new variable reordering heuristic that is based on sampling. A small OBDD sample is chosen from the OBDDs that are considered for minimization. Solving the problem for this small sample, we obtain a variable order that is extrapolated and applied to the entire OBDDs. We present the first experimental results with the Sample Reordering targeted at combinatorial verification. The suggested heuristic is substantially faster than Sifting.