Proceedings of 2013 International Conference on Information Science and Computer Applications

Regression Testing for Automatic Fare Collection System of Rail Transit

Authors
Mo Cheng, Maolin Zhang
Corresponding Author
Mo Cheng
Available Online October 2013.
DOI
10.2991/isca-13.2013.54How to use a DOI?
Keywords
regression testing; automatic fare collection system; cluster analysis; risk assessment; code analysis; functional model
Abstract

Since regression testing technologies are mainly for software systems, there are few research about the access detecting of the auto fare collection system in rail transit. This paper study the multi-level functional modeling, the source code importing of detected object, the historical test information collection, the test of risk assessment of used cases and cluster selection techniques, and integration of those techniques and further study, which aims to put forward a set of complete regression testing method and to implement a suitable regression testing management tool for the access detecting of the automatic fare collection system in rail transit, which is to verify the correctness and feasibility of this method.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of 2013 International Conference on Information Science and Computer Applications
Series
Advances in Intelligent Systems Research
Publication Date
October 2013
ISBN
10.2991/isca-13.2013.54
ISSN
1951-6851
DOI
10.2991/isca-13.2013.54How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Mo Cheng
AU  - Maolin Zhang
PY  - 2013/10
DA  - 2013/10
TI  - Regression Testing for Automatic Fare Collection System of Rail Transit
BT  - Proceedings of 2013 International Conference on Information Science and Computer Applications
PB  - Atlantis Press
SP  - 316
EP  - 326
SN  - 1951-6851
UR  - https://doi.org/10.2991/isca-13.2013.54
DO  - 10.2991/isca-13.2013.54
ID  - Cheng2013/10
ER  -