Selection of optimum test points set for analog faults dictionary techniques

The problem of minimum test points set selection for analog fault dictionary is formulated as an optimal decision tree construction problem. Proposed approach is based on integrating concepts from information theory and heuristic graph search methods. Lower bounds on the optimal heuristic evaluation function from the M-ary code rule and information-theoretic concepts of entropy are derived. These lower bounds ensure that a global minimum test points set is found. The heuristic search algorithm avoided the blindness in the search progress and in turn has higher computational efficiency than exhaustive search algorithm. Statistical experiments are carried out in the end, compared with the time and space complicated degree of the exhaustive method, the proposed algorithm is more shortcuts. Therefore, it is a good solution to minimize the size of test points set.