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Title

Adaptive random testing by localization

Author(s)

Chen, Tsong Yueh;  Huang, Dehao H.

Abstract

Based on the intuition that widely spread test cases should have greater chance of hitting the nonpoint failure-causing regions, several adaptive random testing (ART) methods have recently been proposed to improve traditional random testing (RT). However, most of the ART methods require additional distance computations to ensure an even spread of test cases. In this paper, we introduce the concept of localization that can be integrated with some ART methods to reduce the distance computation overheads. By localization, test cases would be selected from part of the input domain instead of the whole input domain, and distance computation would be done for some instead of all previous test cases. Our empirical results show that the fault detecting capability of our method is comparable to those of other ART methods.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies

Source

Proceedings of the 11th Asia-Pacific Software Engineering Conference, Busan, Korea, 30 November - 03 December 2004, pp. 292-298

Publication year

2004

Keyword(s)

Adaptive random testing;  Localization;  Random testing

Publisher

IEEE Computer Society

Publisher URL

http://dx.doi.org/10.1109/APSEC.2004.17

Copyright

Copyright © 2004 IEEE. Published version of the paper reproduced here in accordance with the copyright policy of the publisher. 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 to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Full text

Peer reviewed