Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing

Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Alg...

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Main Author:	S. Ahmed, Bestoun
Format:	Thesis
Language:	English
Published:	2011
Subjects:	TK1-9971 Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.usm.my/46326/1/BESTOUN%20S.%20AHMED_HJ.pdf
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id	my-usm-ep.46326
record_format	uketd_dc
spelling	my-usm-ep.463262020-02-25T07:42:34Z Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing 2011-12 S. Ahmed, Bestoun TK1-9971 Electrical engineering. Electronics. Nuclear engineering Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Algorithm, and Tabu Search. Although useful, most existing AI-based strategies adopt complex search processes and require heavy computations. For this reason, existing AI-based strategies have been confined to small interaction strengths (i.e., t≤3) and small test configurations. Recent studies demonstrate the need to go up to t=6 in order to capture most faults. This thesis presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t=6. The performance of PSTG is evaluated using several sets of benchmark experiments. Comparatively, PSTG consistently outperforms its AI counterparts and other existing strategies as far as the size of the test suite is concerned. Furthermore, the case study demonstrates the usefulness of PSTG for detecting faulty interactions of the input components. 2011-12 Thesis http://eprints.usm.my/46326/ http://eprints.usm.my/46326/1/BESTOUN%20S.%20AHMED_HJ.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik & Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	TK1-9971 Electrical engineering Electronics Nuclear engineering
spellingShingle	TK1-9971 Electrical engineering Electronics Nuclear engineering S. Ahmed, Bestoun Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
description	Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Algorithm, and Tabu Search. Although useful, most existing AI-based strategies adopt complex search processes and require heavy computations. For this reason, existing AI-based strategies have been confined to small interaction strengths (i.e., t≤3) and small test configurations. Recent studies demonstrate the need to go up to t=6 in order to capture most faults. This thesis presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t=6. The performance of PSTG is evaluated using several sets of benchmark experiments. Comparatively, PSTG consistently outperforms its AI counterparts and other existing strategies as far as the size of the test suite is concerned. Furthermore, the case study demonstrates the usefulness of PSTG for detecting faulty interactions of the input components.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	S. Ahmed, Bestoun
author_facet	S. Ahmed, Bestoun
author_sort	S. Ahmed, Bestoun
title	Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
title_short	Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
title_full	Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
title_fullStr	Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
title_full_unstemmed	Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
title_sort	adopting a particle swarm-based test generator strategy for variable-strength and t-way testing
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Elektrik & Elektronik
publishDate	2011
url	http://eprints.usm.my/46326/1/BESTOUN%20S.%20AHMED_HJ.pdf
_version_	1747821651966296064

Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing

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