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Low-Power Test Pattern Generation

  • Xiaoqing Wen
  • Seongmoon Wang
Chapter

Abstract

Test pattern generation is an important part of the VLSI testing flow that offers many possibilities that can be explored for reducing test power dissipation. The issue of test power reduction can be addressed at various stages of test generation for logic circuits, by employing low-power automatic test pattern generation, low-power test compaction, low-power X-filling, and low-power test vector ordering. In addition, power dissipation in memory testing can be reduced through low-power memory test generation. The most significant advantage of reducing test power through low-power test generation is that this approach causes neither circuit overhead nor performance degradation. However, low-power test generation is a complex technical field, in which many important factors in addition to the effect of test power reduction such as test vector count inflation, potential fault coverage loss, test generation time increase, compatibility with compressed scan testing, and test generation flow modification should be taken into careful consideration. Therefore, the objective of this chapter is to provide a comprehensive overview of the basic principals and fundamental approaches to low-power test generation, along with detailed descriptions of typical methods, so as to help researchers devise more innovative solutions and practitioners build better flows in order to achieve the goal of optimally reducing test power through low-power test generation.

Keywords

Test Vector Test Relaxation Switching Activity Static Random Access Memory Automatic Test Pattern Generation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors wish to thank Dr. P. Girard of LIRMM, Prof. N. Nicolici of McMaster University, Prof. K. K. Saluja of University of Wisconsin – Madison, Prof. S. M. Reddy of University of Iowa, Dr. L.-T. Wang of SynTest Technologies, Inc., Prof. M. Tehranipoor of University of Connecticut, Prof. S. Kajihara and Prof. K. Miyase of Kyushu Institute of Technology, Prof. K. Kinoshita of Osaka Gakuin University, Prof. X. Li and Prof. Y. Hu of Institute of Computing Technology of Chinese Academy of Sciences, Prof. Q. Xu of Chinese University of Hong Kong, Dr. K. Hatayama and Dr. T. Aikyo of STARC, and Prof. J.-L. Huang of National Taiwan University for reviewing this chapter and providing valuable comments.

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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Kyushu Institute of TechnologyIizukaJapan

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