Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
: Parametric design is an important modeling paradigm in computer aided design. Relationships (constraints) between the degrees of freedom (DOFs) of the model, instead of the DOFs ...
Binary decision diagrams (BDDs) have been shown to be a powerful tool in formal verification. Efficient BDD construction techniques become more important as the complexity of proto...
Bwolen Yang, Yirng-An Chen, Randal E. Bryant, Davi...
In the last two decades we have witnessed an impressive advance in the efficiency of propositional satisfiability techniques (SAT), which has brought large and previously-intractab...
Generic representatives have been proposed for the effective combination of symmetry reduction and symbolic representation with BDDs in non-probabilistic model checking. This appro...