A heuristic for multiple weight set generation

The number of weighted random patterns depends on the number of deterministic test patterns with a low sampling probability. The weight set that is extracted from the deterministic pattern set with high sampling probability reduces the number of test patterns. In this paper we present a new deterministic pattern selection algorithm which generates high performance weight sets by removing deterministic patterns with low sampling frequencies. Simulation results using ISCAS 85 benchmark circuits prove the effectiveness of the new weight set generation algorithm.