Minimizing defective part level using a linear programming-based optimal test selection method

Minimizing defective part level using a linear programming-based optimal test selection method

Recent probabilistic test generation approaches have proven that detecting single stuck-at-faults multiple times is effective at reducing the defective part level (DPL). Unfortunately, these test generation strategies increase the number of test patterns. In this paper, we present a novel linear pro...

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Hauptverfasser: Yuxin Tian, Grimaila, Weiping Shi, Mercer
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Sprache:eng
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Integrated circuit testing
Linear programming
Logic circuit testing
Yield estimation
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Grimaila
Weiping Shi
Mercer
description Recent probabilistic test generation approaches have proven that detecting single stuck-at-faults multiple times is effective at reducing the defective part level (DPL). Unfortunately, these test generation strategies increase the number of test patterns. In this paper, we present a novel linear programming-based method to accelerate the optimal selection of test sets to minimize the defective part level based upon the MPG-D model. Our experimental results show that the proposed method is on average 300 times faster than the existing test pattern selection method.
doi_str_mv 10.1109/ATS.2003.1250836
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subjects Integrated circuit testing
Linear programming
Logic circuit testing
Yield estimation
title Minimizing defective part level using a linear programming-based optimal test selection method
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