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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
White, L.J.: Software testing and verification. Advances in Computers 26, 335–391 (1987)
Hamlet, R.: Random testing. In: Marciniak, J.W. (ed.) Encyclopedia of Software Engineering (1994)
Chan, F.T., Chen, T.Y., Mak, I.K., Yu, Y.T.: Proportional sampling strategy: guidelines for software testing practitioners. Information and Software Technology 38, 775–782 (1996)
Chen, T.Y., Yu, Y.T.: On the relationship between partition and random testing. IEEE Transactions on Software Engineering 20, 977–980 (1994)
White, L.J., Cohen, E.I.: A domain strategy for computer program testing. IEEE Transactions on Software Engineering 6, 247–257 (1980)
Association for Computing Machinery: Collected Algorithms from ACM. Association for Computing Machinery, vol. I, II, III (1980)
Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes. Cambridge University Press, Cambridge (1986)
Freund, J.E.: Modern Elementary Statistics, 5th edn. Prentice-Hall, Englewood Cliffs (1979)
Chen, T.Y., Kuo, F.C., Merkel, R.G., Ng, S.P.: Mirror adaptive random testing. Information and Software Technology (accepted for publication)
Chen, T.Y., Eddy, G., Merkel, R., Wong, P.K.: Adaptive random testing through dynamic partitioning. In: Proceedings of the 4th International Conference on Quality Software (QSIC 2004). IEEE Computer Society Press, Los Alamitos (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, T.Y., Leung, H., Mak, I.K. (2004). Adaptive Random Testing. In: Maher, M.J. (eds) Advances in Computer Science - ASIAN 2004. Higher-Level Decision Making. ASIAN 2004. Lecture Notes in Computer Science, vol 3321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30502-6_23
Download citation
DOI: https://doi.org/10.1007/978-3-540-30502-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24087-7
Online ISBN: 978-3-540-30502-6
eBook Packages: Computer ScienceComputer Science (R0)