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Embedded software-based self-testing for SoC design
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 39th annual Design Automation Conference table of contents
New Orleans, Louisiana, USA
SESSION: New test methods targeting non-classical faults table of contents
Pages: 355 - 360  
Year of Publication: 2002
ISBN ~ ISSN:0738-100X , 1-58113-461-4
Authors
A. Krstic  University of California, Santa Barbara, CA
W. C. Lai  University of California, Santa Barbara, CA
K. T. Cheng  University of California, Santa Barbara, CA
L. Chen  University of California, San Diego, CA
S. Dey  University of California, San Diego, CA
Sponsor
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 34,   Citation Count: 3
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ABSTRACT

At-speed testing of high-speed circuits is becoming increasingly difficult with external testers due to the growing gap between design and tester performance, growing cost of high-performance testers and increasing yield loss caused by inherent tester inaccuracy. Therefore, empowering the chip to test itself seems like a natural solution. Hardware-based self-testing techniques have limitations due to performance and area overhead and problems caused by the application of non-functional patterns.Embedded software-based self-testing has recently become focus of intense research. In this methodology, the programmable cores are used for on-chip test generation, measurement, response analysis and even diagnosis. After the programmable core on a System-on-Chip (SoC) has been self-tested, it can be reused for testing on-chip buses, interfaces and other non-programmable cores. The advantages of this methodology include at-speed testing, low design-for-testability overhead and application of functional patterns in the functional environment. In this paper, we give a survey and outline the roadmap and challenges of this emerging embedded software-based self-testing paradigm.


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:
A. Krstic: colleagues
W. C. Lai: colleagues
K. T. Cheng: colleagues
L. Chen: colleagues
S. Dey: colleagues