Proceedings of the 37th Annual Design Automation Conference
IC Diagnosis Using Multiple Supply Pad IDDQs
IEEE Design & Test
IDDQ Test: Sensitivity Analysis of Scaling
Proceedings of the IEEE International Test Conference on Test and Design Validity
Signature Analysis for IC Diagnosis and Failure Analysis
Proceedings of the IEEE International Test Conference
Diagnosis method based on /spl Delta/Iddq probabilistic signatures: experimental results
ITC '98 Proceedings of the 1998 IEEE International Test Conference
Current signatures [VLSI circuit testing]
VTS '96 Proceedings of the 14th IEEE VLSI Test Symposium
On the Comparison of IDDQ and IDDQ Testing
VTS '99 Proceedings of the 1999 17TH IEEE VLSI Test Symposium
A Process and Technology-Tolerant IDDQ Method for IC Diagnosis
VTS '01 Proceedings of the 19th IEEE VLSI Test Symposium
Current Ratios: A Self-Scaling Technique for Production IDDQ Testing
ITC '99 Proceedings of the 1999 IEEE International Test Conference
Defect Detection Using Quiescent Signal Analysis
Journal of Electronic Testing: Theory and Applications
Quiescent-Signal Analysis: A Multiple Supply Pad IDDQ Method
IEEE Design & Test
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Quiescent Signal Analysis (QSA) is a novel electrical-test-based diagnostic technique that uses IDDQ measurements made at multiple chip supply pads as a means of locating shorting defects in the layout. The use of multiple supply pads reduces the adverse effects of leakage current by scaling the total leakage current over multiple measurements. In previous work, a resistance model for QSA was developed and demonstrated on a small circuit. In this paper, the weaknesses of the original QSA model are identified, in the context of a production power grid (PPG) and probe card model, and a new model is described. The new QSA algorithm is developed from the analysis of IDDQ contour plots. A “family” of hyperbola curves is shown to be a good fit to the contour curves. The parameters to the hyperbola equations are derived with the help of inserted calibration transistors. Simulation experiments are used to demonstrate the prediction accuracy of the method on a PPG.