FAME: a fault-pattern based memory failure analysis framework

Cheng, Kuo-Liang; Wang, Chih-Wea; Lee, Jih-Nung; Chou, Yung-Fa; Huang, Chih-Tsun; Wu, Cheng‐Wen

doi:10.1109/iccad.2003.159743

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2022

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“…Memory diagnosis approaches use various methods to identify and diagnose memory faults, e.g., fault pattern identification [6][7][8], fault signatures [1,9,10]. However, they hardly make any distinction between memory array faults and faults in other parts of the memory, such as decoders and peripherals.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Memory Diagnosis

Medeiros

Fieback

Gebregiorgis

et al. 2022

2022 IEEE European Test Symposium (ETS)

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High-quality memory diagnosis methodologies are critical enablers for scaled memory devices as they reduce time to market and provide valuable information regarding test escapes and customer returns. This paper presents an efficient Hierarchical Memory Diagnosis (HMD) approach that accurately diagnoses faults in the entire memory. Faults are diagnosed hierarchically; first, their location, then their nature (i.e., static or dynamic), and finally, their functional fault model. The HMD approach leads to a more accurate diagnostic, enabling the precise identification of yield loss causes.

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