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Title

Adaptive random testing

Author(s)

Chen, T. Y.

Abstract

Random testing is a basic testing technique. Motivated by the observation that neighboring inputs normally exhibit similar failure behavior, the approach of adaptive random testing has recently been proposed to enhance the fault detection capability of random testing. The intuition of adaptive random testing is to evenly spread the randomly generated test cases. Experimental results have shown that adaptive random testing can use as fewer as 50% of test cases required by random testing with replacement to detect the first failure. These results have very significant impact in software testing, because random testing is a basic and popular technique in software testing. In view of such a significant improvement of adaptive random testing over random testing, it is very natural to consider to replace random testing by adaptive random testing. Hence, many works involving random testing may be worthwhile to be reinvestigated using adaptive random testing instead. Obviously, there are different approaches of evenly spreading random test cases. In this tutorial, we are going to present several approaches, and discuss their advantages and disadvantages. Furthermore, the favorable and unfavorable conditions for adaptive random testing would also be discussed. Most existing research on adaptive random testing involves only numeric programs. The recent success of applying adaptive random testing for non-numeric programs would be discussed.

Publication type

Conference abstract

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies

Source

Proceedings of the 8th International Conference on Quality Software (QSIC 08), Oxford, United Kingdom, 12-13 August 2008, p. 443

Publication year

2008

Keyword(s)

Adaptive random testing;  ART;  Failure behaviour;  Fault detection;  Nonnumeric programs;  Program testing;  Random testing;  Randomly-generated test cases;  RT;  Software testing

Publisher

IEEE Computer Society

ISSN

1550-6002 (series ISSN)

ISBN

9780769533124

Publisher URL

http://dx.doi.org/10.1109/QSIC.2008.22

Copyright

Copyright © 2008 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

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