Scan chains are popularly used as the channels for silicon testing and debugging. However, they have also been identified as one of the culprits of silicon failure more recently. To cope with this problem, several scan chain diagnosis approaches have been proposed in the past. The existing methods, however, suffer from one common drawback-that is, they rely on fault models and matching heuristics to locate the faults. Such a paradigm may run into difficulty when the fault under diagnosis does not match the fault model exactly, for example, when there is a bridging between a flip-flop and a logic cell, or the fault is temporal and only manifests itself intermittently. In light of this, we propose in this article a more versatile model-free paradigm for locating the faulty flip-flops in a scan chain, incorporating a number of signal processing techniques, such as filtering and edge detection. These techniques performed on the test responses of the failing chip under diagnosis directly can effectively reveal the fault location(s) in a scan chain. As compared to the previous works, our approach is better capable of handling intermittent faults and bridging faults, even under nonideal conditions, for example, when the core logic is also faulty. Experimental results on several real designs indicate that this approach can indeed catch some nasty faults that previous methods could not catch.

In this paper we address the scan chain diagnosis problem. We propose a new diagnosis flow based on the concept of signal profiling to accurately pinpoint the location of a faulty flip-flop 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 simulate the behaviors of a large number of fault candidates. Also, it is general and applicable to all kinds of faults because it does not assume any specific fault model. Experimental results indicate that this approach can instantly catch a fault within a scan chain quite accurately in most cases.