A data path synthesis method for self-testable designs

Abstract

A high-level synthesis for testability method is presented whose objective is to generate self-testable RTL designs from data flow behavioral descriptions. The approach is formulated as an allocation problem based on an underlying structural testability model and its connection rules. Two allocation techniques have been developed to solve this problem: one based on an efficient heuristic algorithm that generates cost-effective designs, the other based on an integer linear program formulation that generates optimal designs. The allocation algorithms have been implemented, and several benchmark examples are presented.