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A kidney algorithm with elitism for combinatorial testing problem

Bahomaid, Ameen A. and Alsewari, Abdulrahman A. and Kamal Z., Zamli and Alhendawi, Kamal M. and Al-Janabi, Ala Aldeen (2020) A kidney algorithm with elitism for combinatorial testing problem. In: ACM International Conference Proceeding Series, 7th International Conference on Automation and Logistics, ICAL 2020, 22-24 July 2020 , Virtual Mode, China. pp. 6-11.. ISBN 9781450377263

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Abstract

Testing software is an important activity before delivering the software with high quality. Among the various approaches for software testing, Combinatorial interaction testing (CIT) is a proper and alternative testing approach for exhaustive testing that covers all possible interactions for a software's parameters. Generating an efficient test list with the optimal size is the most challenging problem in combinatorial interaction testing. Adopting Artificial Intelligence (AI) algorithms as the main algorithm for CIT strategies to generate the most optimal test lists. Kidney algorithm (KA) is a recent computational AI algorithm with sufficient optimization capability which outperforms the other AI algorithms (such as Genetic Algorithm (GA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), Harmony Search (HS)) from some aspects. Although, KA may be easy to fall into local optima by keeping the worst solutions from the past generation as a new population with the best solutions. This study proposes to embed the elitism in the KA to preserve only the best solutions and swap the worsts by the new random solutions. Experimental results have been evidence that the proposed CIT strategy which called elitist KA Strategy (eKAS) produced sufficiently competitive results as compared with the original KA as well the existing CIT strategies.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Combinatorial interaction testing; Elitism; Kidney algorithm; Meta-heuristic
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Institute of Postgraduate Studies
Faculty of Computing
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 22 Apr 2021 07:13
Last Modified: 22 Apr 2021 07:13
URI: http://umpir.ump.edu.my/id/eprint/31044
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