State assignment based on the reduced dependency theory and recent experimental results

A state assignment method is described. The first step of this method recognizes predictive minimization situations in the control flow graph. It is based on the partition pair theory and privileges the cube collapsing in the next state and output equations with regard to factorization. The second step uses a powerful intersecting face embedding theory in the Boolean lattice. This approach has been implemented by software in the ASYL system, and tested on official as well as industrial examples. The gain in silicon area, critical path, and routing factor with respect to random assignment appears to be the best presently known.<>