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  4. Functional-Like Transition Delay Fault Test-Pattern Generation using a Bayesian-Based Circuit Model
 
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Functional-Like Transition Delay Fault Test-Pattern Generation using a Bayesian-Based Circuit Model

Journal
Proceedings of the European Test Workshop
Journal Volume
2020-May
Date Issued
2020
Author(s)
Chen, C.-Y.
Cheng, C.-H.
JIUN-LANG HUANG  
Chakrabarty, K.
DOI
10.1109/ETS48528.2020.9131591
URI
https://www.scopus.com/inward/record.url?eid=2-s2.0-85089139429&partnerID=40&md5=28558db4d030aef0fe13a0ae1ca8015c
https://scholars.lib.ntu.edu.tw/handle/123456789/559057
Abstract
For high-performance integrated circuits with tight timing budgets, full-scan based transition delay fault (TDF) testing is mandatory to ensure high test quality. However, the discrepancy between the scan test mode and the functional mode is problematic. For example, the elevated switching activity during scan test application may degrade circuit performance and lead to overkill. In this paper, we address this problem by generating functional-like TDF test patterns. First, a Bayesian-based circuit model is constructed; the result is an enumeration of circuit states that closely mimics the functional mode. During test generation, the model guides the backtrace and fault propagation procedures more effectively than the conventional SCOAP or COP measures because reconvergent fanout is implicitly included in the model. Experimental results on processor benchmarks, including a MIPS32 and a RISC-V processor, show that the TDF test set generated using the Bayesian-based circuit model not only is more functional-like, but also achieves higher fault coverage. © 2020 IEEE.
Event(s)
2020 IEEE European Test Symposium, ETS 2020
Subjects
automatic test pattern generation; full-scan; functional-like
Other Subjects
Budget control; Circuit simulation; Delay circuits; Timing circuits; Circuit modeling; Circuit performance; Fault coverages; Fault propagation; High-performance integrated circuits; Switching activities; Test generations; Transition delay faults; Statistical tests
Type
conference paper

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