Hierarchical Memory Diagnosis

G. C. Medeiros, M. Fieback, A. Gebregiorgis, M. Taouil, L. B. Poehls, S. Hamdioui

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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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.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE European Test Symposium, ETS 2022
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages2
ISBN (Electronic)9781665467063
Publication statusPublished - 2022
Event27th IEEE European Test Symposium, ETS 2022 - Barcelona, Spain
Duration: 23 May 202227 May 2022

Publication series

NameProceedings of the European Test Workshop
ISSN (Print)1530-1877
ISSN (Electronic)1558-1780


Conference27th IEEE European Test Symposium, ETS 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Algorithm
  • Diagnosis
  • Fault
  • Memory
  • Test


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