Prediction of Test Pattern Count and Test Data Volume for Scan Architectures under Different Input Channel Configurations

Fong Jyun Tsai, Chong Siao Ye, Kuen Jong Lee, Shi Xuan Zheng, Yu Huang, Wu Tung Cheng, Sudhakar M. Reddy, Mark Kassab, Janusz Rajski, Chen Wang, Justyna Zawada

研究成果: Conference contribution

4 引文 斯高帕斯(Scopus)

摘要

As the complexity of industrial integrated circuits continue to increase rapidly, test data compression has now become a de facto technology for large designs to reduce the overall test cost. During the design for test (DFT) planning, it is critical to understand the impact of using different numbers of input/output test channels on test coverage, test cycles, and test data volume. In this paper, two approaches to predict the test pattern counts and test data volumes with different input channel counts are presented, one with the compression tool able to generate channel-scaling patterns and the other without this capability. The results can be used to determine the scan test configuration that results in the smallest or near smallest test data volume. Experiments on industrial circuits show that the average error rates of pattern count prediction for most circuits are less than 10% for both approaches. The error rates of the predicted smallest data volumes are all less than 3.5%. The total ATPG run time can be reduced by a factor of more than 10X compared to the currently used trial-And-error approach.

原文English
主出版物標題2020 IEEE International Test Conference, ITC 2020
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728191133
DOIs
出版狀態Published - 2020 11月 1
事件2020 IEEE International Test Conference, ITC 2020 - Washington, United States
持續時間: 2020 11月 12020 11月 6

出版系列

名字Proceedings - International Test Conference
2020-November
ISSN(列印)1089-3539

Conference

Conference2020 IEEE International Test Conference, ITC 2020
國家/地區United States
城市Washington
期間20-11-0120-11-06

All Science Journal Classification (ASJC) codes

  • 電氣與電子工程
  • 應用數學

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