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Partitioned n-detection test generation
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Great Lakes Symposium on VLSI archive
Proceedings of the 19th ACM Great Lakes symposium on VLSI table of contents
Boston Area, MA, USA
SESSION: Testing table of contents
Pages 93-98  
Year of Publication: 2009
ISBN:978-1-60558-522-2
Authors
Irith Pomeranz  Purdue University, West Lafayette, IN, USA
Sudhakar M. Reddy  University of Iowa, Iowa City, IA, USA
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

We describe a method for improving the quality of <i>n</i>-detection test sets. Unlike earlier methods for achieving the same goal, the proposed method is based on the conventional definition of the number of detections and uses a conventional <i>n</i>-detection test generation process. Under the proposed method, the set of target faults is partitioned into two or more subsets. <i>n</i>-detection test generation is carried out for each subset separately. The resulting test sets are combined into a single test set. Partitioning causes more faults to be targeted directly, and fewer faults to be dropped due to accidental detection. The fault subsets can be selected based on detection conditions of common defects. In this work we partition the set of faults into a subset that consists of all the stuck-at 0 faults, and a subset that consists of all the stuck-at 1 faults. We demonstrate through experimental results that for the same test set size, partitioning the set of faults improves the coverage of untargeted faults (non-feedback four-way bridging faults) compared to <i>n</i>-detection test generation for the unpartitioned set of faults.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Irith Pomeranz: colleagues
Sudhakar M. Reddy: colleagues