T-Way Test Data Generation Strategy Based on Particle Swarm Optimization
B. Ahmed, and K. Zamli. 0, Kuala Lumpur, Malaysia, IEEE Computer Society, (May 2010)
Abstract
Due to market demands, software has grown tremendously in size and functionalities over the years. As side effects of such growth, there tend to be more and more unwanted interaction between software and system parameters. These unwanted interactions can sometimes lead to nasty and difficult bugs to detect. In order to address these issues, t-way strategies (i.e. where t indicates interaction strength) are helpful to generate a set of test cases (i.e. to form a complete suite) that cover the required interaction strength as least once from a typically large space of possible test values. In this paper, we highlight a new t-way strategy based on Particle Swarm Optimization, called PSTG. Preliminary results demonstrated that PSTG compares well against other existing t-way strategies.
%0 Conference Proceedings
%1 Bestoun
%A Ahmed, Bestoun S.
%A Zamli, Kamal Z.
%C Kuala Lumpur, Malaysia
%D 2010
%E IEEE,
%I IEEE Computer Society
%K Artificial Intelligence Interaction Optimization Particle Swarm Testing t-way
%T T-Way Test Data Generation Strategy Based on Particle Swarm Optimization
%U http://doi.ieeecomputersociety.org/10.1109/ICCRD.2010.56
%V 0
%X Due to market demands, software has grown tremendously in size and functionalities over the years. As side effects of such growth, there tend to be more and more unwanted interaction between software and system parameters. These unwanted interactions can sometimes lead to nasty and difficult bugs to detect. In order to address these issues, t-way strategies (i.e. where t indicates interaction strength) are helpful to generate a set of test cases (i.e. to form a complete suite) that cover the required interaction strength as least once from a typically large space of possible test values. In this paper, we highlight a new t-way strategy based on Particle Swarm Optimization, called PSTG. Preliminary results demonstrated that PSTG compares well against other existing t-way strategies.
@proceedings{Bestoun,
abstract = {Due to market demands, software has grown tremendously in size and functionalities over the years. As side effects of such growth, there tend to be more and more unwanted interaction between software and system parameters. These unwanted interactions can sometimes lead to nasty and difficult bugs to detect. In order to address these issues, t-way strategies (i.e. where t indicates interaction strength) are helpful to generate a set of test cases (i.e. to form a complete suite) that cover the required interaction strength as least once from a typically large space of possible test values. In this paper, we highlight a new t-way strategy based on Particle Swarm Optimization, called PSTG. Preliminary results demonstrated that PSTG compares well against other existing t-way strategies.},
added-at = {2010-09-08T00:41:47.000+0200},
address = {Kuala Lumpur, Malaysia},
author = {Ahmed, Bestoun S. and Zamli, Kamal Z.},
biburl = {https://www.bibsonomy.org/bibtex/23f766a52336300c6f6a4131f96b6e5ff/bestoun},
editor = {IEEE},
interhash = {e8bdebed82adb2528c25c536bbb238e2},
intrahash = {3f766a52336300c6f6a4131f96b6e5ff},
keywords = {Artificial Intelligence Interaction Optimization Particle Swarm Testing t-way},
month = {May 07-May 10},
publisher = {IEEE Computer Society},
timestamp = {2010-09-08T00:42:11.000+0200},
title = {T-Way Test Data Generation Strategy Based on Particle Swarm Optimization},
url = {http://doi.ieeecomputersociety.org/10.1109/ICCRD.2010.56},
volume = 0,
year = 2010
}