Ant Colony Optimization Algorithm Parameter Tuning for T-way IOR Testing

In this study, Ant Colony Optimization (ACO) algorithm's parameters for t-way IOR testing were examined. ACO and its variant have been applied to t-way testing but never to t-way IOR interaction support. Tuning ACO parameters were executed to ensure that ACO could perform for IOR as good as oth...

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Bibliographic Details
Published in:Journal of physics. Conference series Vol. 1019; no. 1; pp. 12086 - 12093
Main Authors: Ramli, N, Othman, R R, Fauzi, S S M
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01.06.2018
Subjects:
Algorithms
Ant colony optimization
Configurations
input-output based relation
Interaction parameters
Physics
t-way testing
Tuning
ISSN:1742-6588, 1742-6596
Online Access:Get full text
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Summary:In this study, Ant Colony Optimization (ACO) algorithm's parameters for t-way IOR testing were examined. ACO and its variant have been applied to t-way testing but never to t-way IOR interaction support. Tuning ACO parameters were executed to ensure that ACO could perform for IOR as good as other t-way interaction support. Parameter α, β, τ0, q0, ρ value and number of ant were tuned to uniform and non-uniform configuration. Each parameter was executed for 10 independent run. Average best test suite and best test suite were recorded and compared among other parameter values to find which value will produce the best result. The optimum test suite size and average test suite size were generated when the value for parameter α = 0.5, β = 3, τ0 = 0.4 (uniform configuration) and, 0.2 and 1 (non-uniform configuration), q0 = 0.5, ρ = 0.5 and number of ant = 20.
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1019/1/012086