With feature sizes steadily shrinking, manufacturing defects and parameter variations often cause design timing failures. It is essential that those errors be correctly and quickly diagnosed. In this paper, we analyze the multiple-delay-fault diagnosis problem and propose a novel approach to solve it. We enhance the diagnostic resolution by processing failure logs at various slower-than-nominal clock frequencies. We evaluate the utility ofn-detection and timing-aware automatic-test-pattern-generated (ATPG) sets. Experimental results show that using timing-aware ATPG sets yields better diagnostic resolution and results in better delay-defect-size estimations compared ton-detection ATPG sets. We experimentally determined our diagnosis algorithm's sensitivity to delay variations.

With feature sizes steadily shrinking, manufacturing defects and parameter variations often cause design-timing failures. It is essential that those errors be correctly and quickly diagnosed. The existing delay-fault diagnosis algorithms cannot identify delay faults that require nonrobust test patterns due to incorrect emulation of the failure analyzer's behavior. We propose a novel approach to performing delay-fault diagnosis for robust and nonrobust tests. We enhance the diagnostic resolution by utilizing passing patterns, processing failure logs at various slower frequencies, and applying n-detection and timing-aware automatic test pattern generation sets. Experimental results show that our approach can diagnose delay faults with good resolution. The algorithm is stable with respect to delay variations that manufactured chips might experience.

With feature sizes shrinking, manufacturing defects and parameter variations often cause design timing failures. Crosstalk coupling is one of such causes. It is essential that timing failures be correctly and quickly diagnosed. The authors present a methodology to diagnose the delay-defect in presence of crosstalk, given the physical information such as crosstalk coupling capacitance, neighborhood information and SDF delay information. The authors provide diagnosis results for 180, 130, 90 and 65 nm technologies