Fast computation of data correlation using BDDs

Abstract

Data correlation is a well-known problem that causes difficulty in VLSI testing. Based on a correlation metric, an efficient heuristic to select BIST registers has been proposed in the previous work. However, the computation of data correlation itself was a computational intensive process and became a bottleneck in the previous work. This paper presents an efficient technique to compute data correlation using Binary Decision Diagrams (BDDs). Once a BDD is built, our algorithms take linear time to compute the corresponding data correlation. The experimental results show that this technique is much faster than the previous technique based on simulation. It enables testing approaches based on data correlation to handle more practical designs. As one of the successful applications, partial scan is demonstrated by integrating our computation results.