Deterministic Diagnostic Pattern Generation (DDPG) for Compound Defects

Abstract

Scan chain failure diagnosis has become an important means for silicon debug and yield improvement. Although plenty of prior work discussed how to perform scan chain diagnosis, most of the previously proposed techniques made an assumption that the system logic is fault-free, which could be an impractical assumption leading to incorrect diagnostic results. In this paper, we propose a scan chain deterministic diagnostic pattern generation (DDPG) method that can tolerate the faults in the system logic without degradation of chain diagnostic resolution and precision. The entire flow includes three steps. In the first step, patterns are created to propagate the state of a targeted scan cell to as many reliable observation points as possible. In the second step, the load error probability of each targeted scan cell is calculated based on the hamming distances between the observed responses and the expected good or faulty responses. In the last step, a suspect profile is plotted, which can be used to identify the suspect scan cell(s) based on ranking scores. Experimental results show that the diagnostic resolution and precision are not degraded even with dozens of faults injected into the system logic.