Published: March 29, 2007
Author(s)
Yu Lei, Raghu Kacker, Richard Kuhn, Vadim Okun, J. Lawrence
Conference
Name: 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS ’07)
Dates: 03/26/2007 - 03/29/2007
Location: Tucson, Arizona, United States
Citation: Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS 2007), pp. 549-556
Most existing work on t-way testing has focused on 2-way (or pairwise) testing, which aims to detect faults caused by interactions between any two parameters. However, faults can also be caused by interactions involving more than two parameters. In this paper, we generalize an existing strategy, called In-Parameter-Order (IPO), from pairwise testing to t-way testing. A major challenge of our generalization effort is dealing with the combinatorial growth of the number of combinations of parameter-values. We describe a t-way testing tool, called FireEye, and discuss design decisions that are made to enable an efficient implementation of the generalized IPO strategy. We also report several experiments that are designed to evaluate the effectiveness of FireEye.
Most existing work on t-way testing has focused on 2-way (or pairwise) testing, which aims to detect faults caused by interactions between any two parameters. However, faults can also be caused by interactions involving more than two parameters. In this paper, we generalize an existing strategy,...
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Most existing work on t-way testing has focused on 2-way (or pairwise) testing, which aims to detect faults caused by interactions between any two parameters. However, faults can also be caused by interactions involving more than two parameters. In this paper, we generalize an existing strategy, called In-Parameter-Order (IPO), from pairwise testing to t-way testing. A major challenge of our generalization effort is dealing with the combinatorial growth of the number of combinations of parameter-values. We describe a t-way testing tool, called FireEye, and discuss design decisions that are made to enable an efficient implementation of the generalized IPO strategy. We also report several experiments that are designed to evaluate the effectiveness of FireEye.
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Keywords
combinatorial testing; software testing; t-way testing
Control Families
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