IEICE TRANSACTIONS on Information
Application of Markov Chain Monte Carlo Random Testing to Test Case Prioritization in Regression Testing
Summary :
This paper proposes the test case prioritization in regression testing. The large size of a test suite to be executed in regression testing often causes large amount of testing cost. It is important to reduce the size of test cases according to prioritized test sequence. In this paper, we apply the Markov chain Monte Carlo random testing (MCMC-RT) scheme, which is a promising approach to effectively generate test cases in the framework of random testing. To apply MCMC-RT to the test case prioritization, we consider the coverage-based distance and develop the algorithm of the MCMC-RT test case prioritization using the coverage-based distance. Furthermore, the MCMC-RT test case prioritization technique is consistently comparable to coverage-based adaptive random testing (ART) prioritization techniques and involves much less time cost.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.9 pp.2219-2226
- Publication Date
- 2012/09/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.2219
- Type of Manuscript
- Special Section PAPER (Special Section on Software Reliability Engineering)
- Category
Authors
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Bo ZHOU, Hiroyuki OKAMURA, Tadashi DOHI, "Application of Markov Chain Monte Carlo Random Testing to Test Case Prioritization in Regression Testing" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 9, pp. 2219-2226, September 2012, doi: 10.1587/transinf.E95.D.2219.
Abstract: This paper proposes the test case prioritization in regression testing. The large size of a test suite to be executed in regression testing often causes large amount of testing cost. It is important to reduce the size of test cases according to prioritized test sequence. In this paper, we apply the Markov chain Monte Carlo random testing (MCMC-RT) scheme, which is a promising approach to effectively generate test cases in the framework of random testing. To apply MCMC-RT to the test case prioritization, we consider the coverage-based distance and develop the algorithm of the MCMC-RT test case prioritization using the coverage-based distance. Furthermore, the MCMC-RT test case prioritization technique is consistently comparable to coverage-based adaptive random testing (ART) prioritization techniques and involves much less time cost.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2219/_p
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@ARTICLE{e95-d_9_2219,
author={Bo ZHOU, Hiroyuki OKAMURA, Tadashi DOHI, },
journal={IEICE TRANSACTIONS on Information},
title={Application of Markov Chain Monte Carlo Random Testing to Test Case Prioritization in Regression Testing},
year={2012},
volume={E95-D},
number={9},
pages={2219-2226},
abstract={This paper proposes the test case prioritization in regression testing. The large size of a test suite to be executed in regression testing often causes large amount of testing cost. It is important to reduce the size of test cases according to prioritized test sequence. In this paper, we apply the Markov chain Monte Carlo random testing (MCMC-RT) scheme, which is a promising approach to effectively generate test cases in the framework of random testing. To apply MCMC-RT to the test case prioritization, we consider the coverage-based distance and develop the algorithm of the MCMC-RT test case prioritization using the coverage-based distance. Furthermore, the MCMC-RT test case prioritization technique is consistently comparable to coverage-based adaptive random testing (ART) prioritization techniques and involves much less time cost.},
keywords={},
doi={10.1587/transinf.E95.D.2219},
ISSN={1745-1361},
month={September},}
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TY - JOUR
TI - Application of Markov Chain Monte Carlo Random Testing to Test Case Prioritization in Regression Testing
T2 - IEICE TRANSACTIONS on Information
SP - 2219
EP - 2226
AU - Bo ZHOU
AU - Hiroyuki OKAMURA
AU - Tadashi DOHI
PY - 2012
DO - 10.1587/transinf.E95.D.2219
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2012
AB - This paper proposes the test case prioritization in regression testing. The large size of a test suite to be executed in regression testing often causes large amount of testing cost. It is important to reduce the size of test cases according to prioritized test sequence. In this paper, we apply the Markov chain Monte Carlo random testing (MCMC-RT) scheme, which is a promising approach to effectively generate test cases in the framework of random testing. To apply MCMC-RT to the test case prioritization, we consider the coverage-based distance and develop the algorithm of the MCMC-RT test case prioritization using the coverage-based distance. Furthermore, the MCMC-RT test case prioritization technique is consistently comparable to coverage-based adaptive random testing (ART) prioritization techniques and involves much less time cost.
ER -
English
