Test Vector Generation Based on Correlation Model for Ratio-Iddq

For ratio-Iddq testing, the test performance is significantly affected by the correlation between two currents of different input patterns as process parameters vary. In this paper we first study the reason for strong correlation between Iddq currents for different test vectors, then build a model to estimate the correlation. Based on this model, we propose three test vector selection methods to improve the fault detection ability of ratio-Iddq testing by selecting test vector pairs with the highest correlation. Hspice simulation showed that the fault detection ability can be improved by as much as an order of magnitude. We also describe a test vector partitioning technique to increase the correlation between Iddq currents of different test vectors.