Abstract
In this thesis, we investigate the scan chain diagnosis problem. A new method based on the concept of signal profiling is proposed to accurately pinpoint the location of faulty flip-flops in a scan chain. As compared to the conventional cause-effect or effect-cause analysis, this approach is much more computationally efficient because it does not have to enumerate the behaviors of a large number of fault candidates. Furthermore, it is robust and applicable to various fault types because it does not assume any specific fault model. Experimental results indicate that this approach can instantly catch flip-flop faults within a scan chain quite accurately in most cases.