Algorithms for multilevel logic optimization
Algorithms for multilevel logic optimization
Combinatorial characterization of read-once formulae
Discrete Mathematics - Special issue on combinatorics and algorithms
On read-once Boolean functions
Poceedings of the London Mathematical Society symposium on Boolean function complexity
Learning Boolean read-once formulas over generalized bases
Journal of Computer and System Sciences
The Fanout Structure of Switching Functions
Journal of the ACM (JACM)
Factoring logic functions using graph partitioning
ICCAD '99 Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design
Factoring boolean functions using graph partitioning
Discrete Applied Mathematics - Special issue: Boolean and pseudo-boolean funtions
An improvement on the complexity of factoring read-once Boolean functions
Discrete Applied Mathematics
Graph Theory, Computational Intelligence and Thought
Factoring Boolean functions using graph partitioning
Discrete Applied Mathematics - Special issue: Boolean and pseudo-boolean funtions
On algebraic expressions of series-parallel and Fibonacci graphs
DMTCS'03 Proceedings of the 4th international conference on Discrete mathematics and theoretical computer science
Lineage processing over correlated probabilistic databases
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Efficient method to compute minimum decision chains of Boolean functions
Proceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI
Sensitivity analysis and explanations for robust query evaluation in probabilistic databases
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
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An approach for factoring general boolean functions was described in GM:99 which is based on graph partitioning algorithms. In this paper, we present a very fast algorithm for recognizing and factoring read-once functions which is needed as a dedicated factoring subroutine to handle the lower levels of that factoring process. The algorithm is based on algorithms for cograph recognition and on checking normality. Our method has been implemented in the SIS environment, and an empirical evaluation is given.