On test syndrome merging for reasoning-based board-level functional fault diagnosis

20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015

Volumn , Issue , 2015, Pages 737-742

  Sun, Zelong ^a   Jiang, Li ^b   Xu, Qiang ^a   Zhang, Zhaobo ^c   Wang, Zhiyuan ^c   Gu, Xinli ^c  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b SHANGHAI JIAO TONG UNIVERSITY   (China)

^c HUAWEI TECHNOLOGIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED DESIGN; DISEASES; KNOWLEDGE MANAGEMENT; LEARNING ALGORITHMS; MACHINE LEARNING; TESTING;

AUTOMATED DIAGNOSIS; DIAGNOSTIC SYSTEMS; DIAGNOSTIC TESTS; DOMAIN KNOWLEDGE; FUNCTIONAL FAILURE; FUNCTIONAL FAULTS; HISTORICAL DATA; STRUCTURAL INFORMATION;

MERGING;

EID: 84926444257     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ASPDAC.2015.7059098     Document Type: Conference Paper

References (12)

1. K. P. Parker. Defect coverage of boundary-scan tests: what does it mean when a boundary-scan test passes? In Proc. IEEE International Test Conference (ITC), pp. 181-189, 2003.
2. Z. Sun, L. Jiang, Q. Xu, Z. Zhang, Z. Wang, and X. Gu. AgentDiag: An agent-assisted diagnostic framework for board-level functional failures. In Proc. IEEE International Test Conference (ITC), pp. 1-8, 2013.
3. T. Satyanarayana, G. Subramanyam, and K.V. Rama Rao. Implementing an expert system for fault diagnosis of electronic equipment. Engineering Applications of Artificial Intelligence, 8(3):355-364, 1995.
4. B. Chess and T. Larrabee. Creating small fault dictionaries. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 18(3):346-356, 1999.
5. Z. Zhang, K. Chakrabarty, Z. Wang, Z. Wang, and X. Gu. Smart diagnosis: Efficient board-level diagnosis and repair using artificial neural networks. In Proc. IEEE International Test Conference (ITC), pp. 1-9, 2011.
6. D. M. Hawkins. The problem of overfitting. Journal of chemical information and computer sciences, 44(1):1-12, 2004.
7. F. Ye, Z. Zhang, K. Chakrabarty, and X. Gu. Information-theoretic syndrome and root-cause analysis for guiding board-level fault diagnosis. In Proc. IEEE European Test Symposium (ETS), pp. 1-6, 2013.
8. G. Brown, A. Pocock, M.J. Zhao, and M. Lujan. Conditional likelihood maximisation: A unifying framework for information theoretic feature selection. The Journal of Machine Learning Research, 13:27-66, 2012.
9. Z. Zhang, X. Gu, Y. Xie, Z. Wang, Z. Wang, and K. Chakrabarty. Diagnostic system based on support-vector machines for board-level functional diagnosis. In Proc. IEEE European Test Symposium, 2012.
10. H. Peng, F. Long, and C. Ding. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8):1226-1238, 2005.
11. C. D. Manning, P. Raghavan, and H. Schutze. Introduction to information retrieval, volume 1. Cambridge university press Cambridge, 2008.
12. Z. Zhang, Z. Wang, X. Gu, and K. Chakrabarty. Physical defect modeling for fault insertion in system reliability test. In Proc. IEEE International Test Conference, pp. 1-10, 2009.