Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing

Software testing is a critical part of software development. Often, test suite sizes grow significantly with subsequent modifications to the software over time resulting into potential redundancies. Test redundancies are undesirable as they incur costs and are not helpful to detect new bugs. Owing t...

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Main Authors:	Kamal Z., Zamli, Norasyikin, Safieny, Fakhrud, Din
Format:	Conference or Workshop Item
Language:	English
Published:	Association for Computing Machinery 2018
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/20924/ http://umpir.ump.edu.my/id/eprint/20924/ http://umpir.ump.edu.my/id/eprint/20924/7/Hybrid%20Test%20Redundancy%20Reduction%20Strategy1.pdf

id	ump-20924
recordtype	eprints
spelling	ump-209242018-08-07T06:51:30Z http://umpir.ump.edu.my/id/eprint/20924/ Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing Kamal Z., Zamli Norasyikin, Safieny Fakhrud, Din QA75 Electronic computers. Computer science Software testing is a critical part of software development. Often, test suite sizes grow significantly with subsequent modifications to the software over time resulting into potential redundancies. Test redundancies are undesirable as they incur costs and are not helpful to detect new bugs. Owing to time and resource constraints, test suite minimization strategies are often sought to remove those redundant test cases in an effort to ensure that each test can cover as much requirements as possible. There are already many works in the literature exploiting the greedy computational algorithms as well as the meta-heuristic algorithms, but no single strategy can claim dominance in terms of test data reduction over their counterparts. Furthermore, despite much useful work, existing strategies have not sufficiently explored the hybrid based meta-heuristic strategies. In order to improve the performance of existing strategies, hybridization is seen as the key to exploit the strength of more than one meta-heuristic algorithm. Given such prospects, this research explores a hybrid test redundancy reduction strategy based on Global Neighborhood Algorithm and Simulated Annealing, called GNA_SA. Overall, GNA_SA offers better reduction as compared to the original GNA and many existing works. Association for Computing Machinery 2018-02 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/20924/7/Hybrid%20Test%20Redundancy%20Reduction%20Strategy1.pdf Kamal Z., Zamli and Norasyikin, Safieny and Fakhrud, Din (2018) Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing. In: Proceedings of the 7th International Conference on Software and Computer Applications (ICSCA 2018), 8-10 February 2018 , Kuantan, Pahang, Malaysia. pp. 87-91.. ISBN 978-145035414-1 http://www.icsca.org/index.html
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 Kamal Z., Zamli Norasyikin, Safieny Fakhrud, Din Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
description	Software testing is a critical part of software development. Often, test suite sizes grow significantly with subsequent modifications to the software over time resulting into potential redundancies. Test redundancies are undesirable as they incur costs and are not helpful to detect new bugs. Owing to time and resource constraints, test suite minimization strategies are often sought to remove those redundant test cases in an effort to ensure that each test can cover as much requirements as possible. There are already many works in the literature exploiting the greedy computational algorithms as well as the meta-heuristic algorithms, but no single strategy can claim dominance in terms of test data reduction over their counterparts. Furthermore, despite much useful work, existing strategies have not sufficiently explored the hybrid based meta-heuristic strategies. In order to improve the performance of existing strategies, hybridization is seen as the key to exploit the strength of more than one meta-heuristic algorithm. Given such prospects, this research explores a hybrid test redundancy reduction strategy based on Global Neighborhood Algorithm and Simulated Annealing, called GNA_SA. Overall, GNA_SA offers better reduction as compared to the original GNA and many existing works.
format	Conference or Workshop Item
author	Kamal Z., Zamli Norasyikin, Safieny Fakhrud, Din
author_facet	Kamal Z., Zamli Norasyikin, Safieny Fakhrud, Din
author_sort	Kamal Z., Zamli
title	Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
title_short	Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
title_full	Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
title_fullStr	Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
title_full_unstemmed	Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
title_sort	hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
publisher	Association for Computing Machinery
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/20924/ http://umpir.ump.edu.my/id/eprint/20924/ http://umpir.ump.edu.my/id/eprint/20924/7/Hybrid%20Test%20Redundancy%20Reduction%20Strategy1.pdf
first_indexed	2023-09-18T22:30:28Z
last_indexed	2023-09-18T22:30:28Z
_version_	1777416251133394944

Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing

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