Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/74103

Title

Adaptive random testing

Author(s)

Chen, T. Y.;  Leung, H.;  Mak, I. K.

Abstract

In this paper, we introduce an enhanced form of random testing called Adaptive Random Testing. Adaptive random testing seeks to distribute test cases more evenly within the input space. It is based on the intuition that for non-point types of failure patterns, an even spread of test cases is more likely to detect failures using fewer test cases than ordinary random testing. Experiments are performed using published programs. Results show that adaptive random testing does outperform ordinary random testing significantly (by up to as much as 50%) for the set of programs under study. These results are very encouraging, providing evidences that our intuition is likely to be useful in improving the effectiveness of random testing.

Publication type

Conference paper

Research centre

Swinburne University of Technology. School of Information Technology

Source

Lecture Notes in Computer Science: Advances in Computer Science: proceedings of the 9th Asian Computing Science Conference: Higher-Level Decision Making (ASIAN 2004), Chiang Mai, Thailand, 08-10 December 2004 / M. J. Maher (ed.), Vol. 3321, pp. 320-329

Publication year

2004

Keyword(s)

Adaptive random testing;  Failure patterns;  Test cases

Publisher

Springer

ISSN

0302-9743 (series ISSN)

ISBN

9783540240877, 354024087X

Publisher URL

http://dx.doi.org/10.1007/b103476

Copyright

Copyright © 2004 Springer-Verlag Berlin Heidelberg.

Peer reviewed