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This work proposes a wafer probe parametric test set optimization method for predicting dies which are likely to fail in the field based on known in-field or final test fails. Large volumes of wafer probe data across 5 lots and hundreds of parametric measurements are optimized to find test sets that help predict actually observed test escapes and final test failures. Simple rules are generated to...
This work proposes a methodology to minimize the application cost of outlier analysis when applied to delay testing in the presence of systematic variability. Support vector machine (SVM) outlier analysis algorithms and traditional entropy measures are used to detect delay defects by choosing a minimum number of suitable test clocks. Monte Carlo simulations generate realistic test data while information...
This work provides a survey study of several outlier analysis techniques and compares their effectiveness in the context of delay testing. Three different approaches are studied, an Euclidean-distance based algorithm, random forest, and one-class support vector machine (SVM), from which more advanced methods are derived and analyzed. We conclude that one-class SVM using a polynomial kernel is most...
Extensive software-based simulation continues to be the mainstream methodology for functional verification of designs. To optimize the use of limited simulation resources, coverage metrics are essential to guide the development of effective test suites. Traditional coverage metrics are defined based on either a functional model or a structural model of the design. If our goal is to select a subset...
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