Competitive group testing and learning hidden vertex covers with minimum adaptivity
FCT'09 Proceedings of the 17th international conference on Fundamentals of computation theory
Bounds for nonadaptive group tests to estimate the amount of defectives
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part II
Randomized group testing both query-optimal and minimal adaptive
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
Self-healing reconfigurable logic using autonomous group testing
Microprocessors & Microsystems
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We examine the general problem of built-in-self-test (BIST) diagnosis in digital logic systems. The BIST diagnosis problem has applications that include identification of erroneous test vectors, faulty scan cells, and faulty items. We develop an abstract model of this problem and show a fundamental correspondence to the well-established subject of combinatorial group testing (CGT) (D. Du and F. K. Hwang, Combinatorial Group Testing and Its Applications, 1994). We exploit this new perspective to 1) link existing BIST diagnosis techniques to CGT techniques and provide further insights into existing diagnosis algorithms, 2) improve the performance of diagnosis algorithms, and 3) develop new techniques to address the BIST diagnosis problem. Using the ISCAS'89 benchmarks, we empirically demonstrate the effectiveness of our proposed techniques over existing BIST diagnosis techniques. The vastness of the CGT literature suggests that further improvements from existing research in CGT may be obtained.