LOT: Logic optimization with testability - new transformations using recursive learning

A new approach to optimize multi-level logic circuits is introduced. Given a multi-level circuit, the synthesis method optimizes its area, simultaneously enhancing its random pattern testability. The method is based on structural transformations at the gate level. New transformations involving EX-OR gates derived based on indirect implications by Recursive Learning have been introduced in the synthesis of multi-level circuits. This method is augmented with transformations that specifically enhance random-pattern testability while reducing the area. Testability enhancement is an integral part of our synthesis methodology. Experimental results show that the proposed methodology can not only realize lower area, but also achieves better testability compared to testability enhancement synthesis tools such as tstfx. Specifically for ISCAS-85 benchmark circuits, it was observed that EX-OR gate-based transformations can yield smaller circuits compared to state-of-the-art logic optimization tools like SIS and HANNIBAL.