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

• Published in: Journal of Physics: Conference Series
• Main Author: Ramli N.; Othman R.R.; Fauzi S.S.M.
• Format: Conference paper
• Language: English
• Published: Institute of Physics Publishing 2018
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049918600&doi=10.1088%2f1742-6596%2f1019%2f1%2f012086&partnerID=40&md5=13ad0dfe814e17440227fd1f792109d4

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. © Published under licence by IOP Publishing Ltd.