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Title

Adaptive random testing with CG constraint

Author(s)

Chan, F. T.;  Chan, Kwok Ping;  Chen, Tsong Yueh;  Yiu, S. M.

Abstract

We introduce a C.G. constraint on adaptive random testing (ART) for programs with numerical input. One rationale behind adaptive random testing is to have the test candidates to be as widespread over the input domain as possible. However, the computation may be quite expensive in some cases. The C.G. constraint is introduced to maintain the widespreadness while reducing the computation requirement in terms of number of distance measures. Three variations of C.G. constraints and their performance when compared with ART are discussed.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies

Source

Paper presented to the 28th Annual International Computer Software and Applications Conference (COMPSAC 2004), Vol. 2 (2004), pp. 96-99

Publication year

2004

Publisher

IEEE Computer Society

Publisher URL

http://dx.doi.org/10.1109/CMPSAC.2004.1342685

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