Title :
Perspectives on Test Data Mining from Industrial Experience
Author_Institution :
Design Technol. Dept., MediaTek Inc., Hsinchu, Taiwan
Abstract :
This paper offers some perspectives on the practice of data mining based on recent experimental research work to establish a link between system-level failures and structural scan test patterns. Beyond the obvious goal to obtain accurate results, knowledge discovery and data insights deserve equal if not higher emphasis. Domain knowledge plays a crucial role in guiding the use of multiple machine learning tools through the fog of data noise towards usable results. A description of data analysis performed on a 28-nm 1.2-GHz quad-core mobile processor serves to illustrate the perspectives.
Keywords :
boundary scan testing; data analysis; data mining; learning (artificial intelligence); microprocessor chips; data analysis; data mining; frequency 1.2 GHz; machine learning tools; quad-core mobile processor; size 28 nm; structural scan test; system-level failures; Data collection; Data mining; Histograms; Production; Radio frequency; Stress; System-on-chip; SOMAC methodology; data mining; higher-than-at-speed test; low-voltage test; machine learning; on-chip-clock patterns; structural scan test; system-level test;
Conference_Titel :
Test Symposium (ATS), 2014 IEEE 23rd Asian
Conference_Location :
Hangzhou
DOI :
10.1109/ATS.2014.52
