A heuristic fault based optimization approach to reduce test vectors count in VLSI testing
In this work we have proposed a heuristic approach to reduce the test vector count during VLSI testing of standard ISCAS circuits. With the shrinking die-space and increasing circuitry on a single Integrated circuit, the number of test vectors required for testing is also increasing. The number of t...
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doaj-d79b45f6a5f5447ca75972d67d28db642020-11-25T00:36:28ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782019-04-01312229234A heuristic fault based optimization approach to reduce test vectors count in VLSI testingVinod Kumar Khera0R.K. Sharma1A.K. Gupta2Corresponding author.; Atmel R&D India Pvt Limited, #643, Regus Business Centre, Sector 16A, Noida, Uttar Pradesh, IndiaAtmel R&D India Pvt Limited, #643, Regus Business Centre, Sector 16A, Noida, Uttar Pradesh, IndiaAtmel R&D India Pvt Limited, #643, Regus Business Centre, Sector 16A, Noida, Uttar Pradesh, IndiaIn this work we have proposed a heuristic approach to reduce the test vector count during VLSI testing of standard ISCAS circuits. With the shrinking die-space and increasing circuitry on a single Integrated circuit, the number of test vectors required for testing is also increasing. The number of test vectors directly affects the total testing cost of a circuit. In this work fault based test vector optimization has been proposed. Here, test vectors have been reduced by extracting child test vectors and merging them. The proposed scheme helps in reducing the test vector count and has been tested successfully using single stuck at fault models. The results obtained illustrate the effectiveness of proposed scheme. Keywords: VLSI testing, Essential fault based test vector optimization, Independent fault based test vector optimization, Test vector counthttp://www.sciencedirect.com/science/article/pii/S1319157817300423 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Vinod Kumar Khera R.K. Sharma A.K. Gupta |
spellingShingle |
Vinod Kumar Khera R.K. Sharma A.K. Gupta A heuristic fault based optimization approach to reduce test vectors count in VLSI testing Journal of King Saud University: Computer and Information Sciences |
author_facet |
Vinod Kumar Khera R.K. Sharma A.K. Gupta |
author_sort |
Vinod Kumar Khera |
title |
A heuristic fault based optimization approach to reduce test vectors count in VLSI testing |
title_short |
A heuristic fault based optimization approach to reduce test vectors count in VLSI testing |
title_full |
A heuristic fault based optimization approach to reduce test vectors count in VLSI testing |
title_fullStr |
A heuristic fault based optimization approach to reduce test vectors count in VLSI testing |
title_full_unstemmed |
A heuristic fault based optimization approach to reduce test vectors count in VLSI testing |
title_sort |
heuristic fault based optimization approach to reduce test vectors count in vlsi testing |
publisher |
Elsevier |
series |
Journal of King Saud University: Computer and Information Sciences |
issn |
1319-1578 |
publishDate |
2019-04-01 |
description |
In this work we have proposed a heuristic approach to reduce the test vector count during VLSI testing of standard ISCAS circuits. With the shrinking die-space and increasing circuitry on a single Integrated circuit, the number of test vectors required for testing is also increasing. The number of test vectors directly affects the total testing cost of a circuit. In this work fault based test vector optimization has been proposed. Here, test vectors have been reduced by extracting child test vectors and merging them. The proposed scheme helps in reducing the test vector count and has been tested successfully using single stuck at fault models. The results obtained illustrate the effectiveness of proposed scheme. Keywords: VLSI testing, Essential fault based test vector optimization, Independent fault based test vector optimization, Test vector count |
url |
http://www.sciencedirect.com/science/article/pii/S1319157817300423 |
work_keys_str_mv |
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1725305123913072640 |