Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing

Migrating Birds Optimization Algorithm (MBO) has gained popularity in solving various engineering problems because it yielded a good and consistent result. In this paper, we combined MBO and elitism to solve the Combinatorial Interaction Testing (CIT) problem i.e. to find a set of minimum test case...

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Main Authors:	Hasneeza, L. Zakaria, Kamal Z., Zamli
Format:	Article
Language:	English
Published:	UTM Press 2017
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/25092/ http://umpir.ump.edu.my/id/eprint/25092/1/Elitism%20Based%20Migrating%20Birds%20Optimization.pdf

id	ump-25092
recordtype	eprints
spelling	ump-250922019-06-13T04:42:45Z http://umpir.ump.edu.my/id/eprint/25092/ Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing Hasneeza, L. Zakaria Kamal Z., Zamli QA75 Electronic computers. Computer science Migrating Birds Optimization Algorithm (MBO) has gained popularity in solving various engineering problems because it yielded a good and consistent result. In this paper, we combined MBO and elitism to solve the Combinatorial Interaction Testing (CIT) problem i.e. to find a set of minimum test case which is an NP-Complete problem. This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. MBO with elitism for solving CIT problem. Elitism is a preservation method that preserves the best population and introduces it back into the next population. Here, we used elitism to preserve the best test cases in order to improve the effectiveness of MBO in generating the minimum set of test cases. This strategy is named as MBO Testing Strategy with elitism (MTS-e). As a comparison with the original MBO we also developed a strategy without elitism, namely MBO Testing Strategy (MTS). MTS yielded a comparable result to the benchmark strategies while MTS-e outperformed most of the benchmarked strategies. The experimental result shows that elitism enhanced the performance of MBO as the mean of the best generated test cases for MTS-e is better than the mean generated by benchmarked strategies. UTM Press 2017 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25092/1/Elitism%20Based%20Migrating%20Birds%20Optimization.pdf Hasneeza, L. Zakaria and Kamal Z., Zamli (2017) Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing. International Journal of Software Engineering and Technology, 3 (1). pp. 10-18.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Hasneeza, L. Zakaria Kamal Z., Zamli Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
description	Migrating Birds Optimization Algorithm (MBO) has gained popularity in solving various engineering problems because it yielded a good and consistent result. In this paper, we combined MBO and elitism to solve the Combinatorial Interaction Testing (CIT) problem i.e. to find a set of minimum test case which is an NP-Complete problem. This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. MBO with elitism for solving CIT problem. Elitism is a preservation method that preserves the best population and introduces it back into the next population. Here, we used elitism to preserve the best test cases in order to improve the effectiveness of MBO in generating the minimum set of test cases. This strategy is named as MBO Testing Strategy with elitism (MTS-e). As a comparison with the original MBO we also developed a strategy without elitism, namely MBO Testing Strategy (MTS). MTS yielded a comparable result to the benchmark strategies while MTS-e outperformed most of the benchmarked strategies. The experimental result shows that elitism enhanced the performance of MBO as the mean of the best generated test cases for MTS-e is better than the mean generated by benchmarked strategies.
format	Article
author	Hasneeza, L. Zakaria Kamal Z., Zamli
author_facet	Hasneeza, L. Zakaria Kamal Z., Zamli
author_sort	Hasneeza, L. Zakaria
title	Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
title_short	Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
title_full	Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
title_fullStr	Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
title_full_unstemmed	Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
title_sort	elitism based migrating birds optimization algorithm for optimization testing
publisher	UTM Press
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/25092/ http://umpir.ump.edu.my/id/eprint/25092/1/Elitism%20Based%20Migrating%20Birds%20Optimization.pdf
first_indexed	2023-09-18T22:38:21Z
last_indexed	2023-09-18T22:38:21Z
_version_	1777416747150737408

Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing

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