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Does adaptive random testing deliver a higher confidence than random testing?

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conference contribution
posted on 2024-11-23, 05:56 authored by Tsong Yueh Chen, Fei Ching Kuo, Huai Liu, Eric Wong
Random testing (RT) is a fundamental software testing technique. Motivated by the rationale that neighbouring test cases tend to cause similar execution behaviours, adaptive random testing (ART) was proposed as an enhancement of RT which enforces random test cases evenly spread over the input domain. ART has always been compared with RT from the perspective of the failure-detection capability. Previous studies have shown that ART can use fewer test cases to detect the first software failure than RT In this paper we aim to compare ART and RT from the perspective of program-based coverage. Our experimental results show that given the same number of test cases, ART normally has a higher percentage of coverage than RT In conclusion, ART outperforms RT not only in terms of the failure detection capability, but also in terms of the thoroughness of program-based coverage. Therefore, ART delivers a higher confidence of the software under test than RT even when no failure has been revealed.

History

Start page

145

End page

154

Total pages

10

Outlet

Proceedings of the 8th International Conference on Quality Software (QSIC 2008)

Editors

Hong Zhu

Name of conference

QSIC 2008

Publisher

IEEE

Place published

Los Alamitos, CA, USA

Start date

2008-08-12

End date

2008-08-13

Language

English

Copyright

© 2008 IEEE.

Notes

© 2008 IEEE. Reprinted, with permission, from Chen, T, Kuo, F, Liu, H and Wong, E 2008, 'Does adaptive random testing deliver a higher confidence than random testing?', in Marie-Claude Gaudel (ed.) Proceedings of the 8th International Conference on Quality Software (QSIC 2008), Los Alamitos, CA, USA, 12-13 August 2008, pp. 145-154. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of RMIT University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Former Identifier

2006040974

Esploro creation date

2020-06-22

Fedora creation date

2013-05-13

Open access

  • Yes

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