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Automatic generation of stimuli for fault diagnosis in IEEE 1687 networks

Cantoro, R.; Montazeri, M.; Sonza, M.; Ghani Zadegan, F. LU and Larsson, Erik LU (2016) 22nd IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2016 In 2016 IEEE 22nd International Symposium on On-Line Testing and Robust System Design, IOLTS 2016 p.167-172
Abstract

The IEEE 1687 standard describes reconfigurable structures allowing to flexibly access the instruments existing within devices (e.g., to support test, debug, calibration, etc.), by the use of configurable modules acting as controllable switches. The increasing adoption of this standard requires the availability of algorithms and tools to automate its usage. Since the resulting networks could inevitably be affected by defects which may prevent their correct usage, solutions allowing not only to test against these defects, but also to diagnose them (i.e., to identify the location of possible faults) are of uttermost importance. This paper proposes a method to automatically generate suitable test stimuli: by applying them and observing the... (More)

The IEEE 1687 standard describes reconfigurable structures allowing to flexibly access the instruments existing within devices (e.g., to support test, debug, calibration, etc.), by the use of configurable modules acting as controllable switches. The increasing adoption of this standard requires the availability of algorithms and tools to automate its usage. Since the resulting networks could inevitably be affected by defects which may prevent their correct usage, solutions allowing not only to test against these defects, but also to diagnose them (i.e., to identify the location of possible faults) are of uttermost importance. This paper proposes a method to automatically generate suitable test stimuli: by applying them and observing the output of the network one can not only detect possible faults, but also identify the fault responsible for the misbehavior. Experimental results gathered on a set of benchmark networks with a prototypical tool implementing the proposed techniques show the feasibility and provide a first idea about the length of the required input stimuli.

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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2016 IEEE 22nd International Symposium on On-Line Testing and Robust System Design, IOLTS 2016
pages
6 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
22nd IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2016
external identifiers
  • scopus:84997447836
ISBN
9781509015061
DOI
10.1109/IOLTS.2016.7604692
language
English
LU publication?
yes
id
36d30f43-9562-43cc-a5dc-0bae3e280b67
date added to LUP
2016-12-12 14:06:52
date last changed
2017-06-25 04:57:19
@inproceedings{36d30f43-9562-43cc-a5dc-0bae3e280b67,
  abstract     = {<p>The IEEE 1687 standard describes reconfigurable structures allowing to flexibly access the instruments existing within devices (e.g., to support test, debug, calibration, etc.), by the use of configurable modules acting as controllable switches. The increasing adoption of this standard requires the availability of algorithms and tools to automate its usage. Since the resulting networks could inevitably be affected by defects which may prevent their correct usage, solutions allowing not only to test against these defects, but also to diagnose them (i.e., to identify the location of possible faults) are of uttermost importance. This paper proposes a method to automatically generate suitable test stimuli: by applying them and observing the output of the network one can not only detect possible faults, but also identify the fault responsible for the misbehavior. Experimental results gathered on a set of benchmark networks with a prototypical tool implementing the proposed techniques show the feasibility and provide a first idea about the length of the required input stimuli.</p>},
  author       = {Cantoro, R. and Montazeri, M. and Sonza, M. and Ghani Zadegan, F. and Larsson, Erik},
  booktitle    = {2016 IEEE 22nd International Symposium on On-Line Testing and Robust System Design, IOLTS 2016},
  isbn         = {9781509015061},
  language     = {eng},
  month        = {10},
  pages        = {167--172},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Automatic generation of stimuli for fault diagnosis in IEEE 1687 networks},
  url          = {http://dx.doi.org/10.1109/IOLTS.2016.7604692},
  year         = {2016},
}