Symbolic Optimization of FSM Networks Based on Sequential ATPG Techniques

This pap er presents a novel optimization algorithm for FSM networks that relies on sequential test generation and redun- dancy removal. The implementation of the prop osed approach, which is based on the exploitation of input don't care sequences through regular language intersection, is fully symb olic. Exp er- imental results, obtained on a large set of standard b enchmarks, improve over the ones of state-of-the-art metho d