On necessary and nonconflicting assignments in algorithmic test pattern generation

Necessary, nonconflicting, and arbitrary assignments can be distinguished during algorithmic test pattern generation. The identification of necessary and nonconflicting assignments is algorithmic in the sense that there is no element of choice or luck in the computation, no reliance on heuristics, and no possibility of these assignments causing a backtrack if the fault is testable. This paper presents algorithms based on the mathematical properties of images and inverse images of set functions to define reduction and tendency lists in combinational logic circuits, used to identify necessary and nonconflicting assignments, respectively. Issues relating to the efficient implementation of these algorithms are addressed from both a theoretical and practical perspective. Experimental results obtained on a variety of benchmark circuits show that algorithmic assignment identification can be used to reduce or eliminate backtracking in automatic test pattern generation