Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory

Testing is one of the main key in advanced semiconductor memory technologies. In the past, memory testing only focuses on fault detection. With the increasing complexity of memory devices, fault diagnosis is becoming very important to locate and identify type of fault. One of the memory faults is N...

Full description

Saved in:
Bibliographic Details
Main Author: Rusli, Julie Roslita
Format: Thesis
Language:English
Published: 2011
Online Access:http://psasir.upm.edu.my/id/eprint/42865/1/FK%202011%20114R.pdf
http://psasir.upm.edu.my/id/eprint/42865/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Putra Malaysia
Language: English
id my.upm.eprints.42865
record_format eprints
spelling my.upm.eprints.428652016-06-27T02:09:06Z http://psasir.upm.edu.my/id/eprint/42865/ Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory Rusli, Julie Roslita Testing is one of the main key in advanced semiconductor memory technologies. In the past, memory testing only focuses on fault detection. With the increasing complexity of memory devices, fault diagnosis is becoming very important to locate and identify type of fault. One of the memory faults is Neighborhood Pattern Sensitive Faults (NPSF). NPSF is one of the faults that are hard to test due to higher number of cells to be tested at one time. Moreover, most of the memory test algorithm does not have the capability to detect and diagnose NPSF. Therefore, the purpose of this thesis is to develop NPSF detection and diagnose software for Static Random Access Memories (SRAM). The development of this Automated NPSF Syndrome Generator (ANPSFSG) is to improve the process of analyzing NPSF detection and to generate the fault syndrome for NPSF diagnosis. This automated generator will facilitate NPSF analysis as manual fault analysis is no longer practical due to increasing memory size. The algorithms used in this generator are based on March algorithm. Three types of March algorithms which are March 17N, March 12N and MarchPS 23N are selected to validate the tool in term of their compatibility for NPSF detection and diagnosis.Suitable data background is identified and a test procedure is developed for each algorithm. All test procedures are integrated into comprehensive database which is developed using Microsoft Access software. The ANPSFSG is able to list detected diagnosed faults as well as to calculate and display fault diagnostic resolution. A user-friendly Graphical User Interface (GUI) is developed using Microsoft Visual Basic software to load and display the algorithm under test and display the result. The results produced by the tools are then validated with other research finding. This tool can be used to ease the process of developing a new March test algorithm for NPSF. 2011-08 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/42865/1/FK%202011%20114R.pdf Rusli, Julie Roslita (2011) Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory. Masters thesis, Universiti Putra Malaysia.
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Testing is one of the main key in advanced semiconductor memory technologies. In the past, memory testing only focuses on fault detection. With the increasing complexity of memory devices, fault diagnosis is becoming very important to locate and identify type of fault. One of the memory faults is Neighborhood Pattern Sensitive Faults (NPSF). NPSF is one of the faults that are hard to test due to higher number of cells to be tested at one time. Moreover, most of the memory test algorithm does not have the capability to detect and diagnose NPSF. Therefore, the purpose of this thesis is to develop NPSF detection and diagnose software for Static Random Access Memories (SRAM). The development of this Automated NPSF Syndrome Generator (ANPSFSG) is to improve the process of analyzing NPSF detection and to generate the fault syndrome for NPSF diagnosis. This automated generator will facilitate NPSF analysis as manual fault analysis is no longer practical due to increasing memory size. The algorithms used in this generator are based on March algorithm. Three types of March algorithms which are March 17N, March 12N and MarchPS 23N are selected to validate the tool in term of their compatibility for NPSF detection and diagnosis.Suitable data background is identified and a test procedure is developed for each algorithm. All test procedures are integrated into comprehensive database which is developed using Microsoft Access software. The ANPSFSG is able to list detected diagnosed faults as well as to calculate and display fault diagnostic resolution. A user-friendly Graphical User Interface (GUI) is developed using Microsoft Visual Basic software to load and display the algorithm under test and display the result. The results produced by the tools are then validated with other research finding. This tool can be used to ease the process of developing a new March test algorithm for NPSF.
format Thesis
author Rusli, Julie Roslita
spellingShingle Rusli, Julie Roslita
Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
author_facet Rusli, Julie Roslita
author_sort Rusli, Julie Roslita
title Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
title_short Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
title_full Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
title_fullStr Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
title_full_unstemmed Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
title_sort development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
publishDate 2011
url http://psasir.upm.edu.my/id/eprint/42865/1/FK%202011%20114R.pdf
http://psasir.upm.edu.my/id/eprint/42865/
_version_ 1643833405425582080