Branch coverage test case generation using genetic algorithm and harmony search

Due to the vital role of software in the modern world, there is a great demand for reliability, and it can be achieved through the process of testing. White-Box testing is one of the testing methods that aims to uncover errors of coding by investigating the internal structure of the software. Moreov...

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Main Author:	Abedinpourshotorban, Hosein
Format:	Thesis
Language:	English
Published:	2015
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/53579/25/HoseinAbedinpourshotorbanMFC2015.pdf
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id	my-utm-ep.53579
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spelling	my-utm-ep.535792020-07-21T08:16:33Z Branch coverage test case generation using genetic algorithm and harmony search 2015-01 Abedinpourshotorban, Hosein QA75 Electronic computers. Computer science Due to the vital role of software in the modern world, there is a great demand for reliability, and it can be achieved through the process of testing. White-Box testing is one of the testing methods that aims to uncover errors of coding by investigating the internal structure of the software. Moreover, generation of test cases for White-Box testing of software can be done manually or automatically. However, due to possible mistakes and expenses of manual test case generation, trend is toward making this activity automatic. So far, proposed techniques for automatic test case generation are mostly based on Genetic Algorithm (GA). However, existing GA techniques are quite slow and unable to achieve full coverage when it comes to test case generation for complex software with a wide range of inputs. Thus, in this research an improved fitness function is proposed based on Control Dependence Graph (CDG) and branch distance that can improve the speed and coverage of test cases generation by the means of evolutionary algorithms like GA. Also, a GA-based branch coverage test case generation technique is proposed in this research that takes advantage of our proposed fitness function, and comparison results based on two benchmark case studies show that our proposed technique outperforms the original CDG technique in speed and coverage of test case generation. In addition, we evaluated our proposed fitness function with harmony search algorithm (HS), which is a more recent optimization algorithm compared to GA, and find out that HS outperforms GA in speed of test case generation for branch coverage of software code. 2015-01 Thesis http://eprints.utm.my/id/eprint/53579/ http://eprints.utm.my/id/eprint/53579/25/HoseinAbedinpourshotorbanMFC2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:84058 masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Abedinpourshotorban, Hosein Branch coverage test case generation using genetic algorithm and harmony search
description	Due to the vital role of software in the modern world, there is a great demand for reliability, and it can be achieved through the process of testing. White-Box testing is one of the testing methods that aims to uncover errors of coding by investigating the internal structure of the software. Moreover, generation of test cases for White-Box testing of software can be done manually or automatically. However, due to possible mistakes and expenses of manual test case generation, trend is toward making this activity automatic. So far, proposed techniques for automatic test case generation are mostly based on Genetic Algorithm (GA). However, existing GA techniques are quite slow and unable to achieve full coverage when it comes to test case generation for complex software with a wide range of inputs. Thus, in this research an improved fitness function is proposed based on Control Dependence Graph (CDG) and branch distance that can improve the speed and coverage of test cases generation by the means of evolutionary algorithms like GA. Also, a GA-based branch coverage test case generation technique is proposed in this research that takes advantage of our proposed fitness function, and comparison results based on two benchmark case studies show that our proposed technique outperforms the original CDG technique in speed and coverage of test case generation. In addition, we evaluated our proposed fitness function with harmony search algorithm (HS), which is a more recent optimization algorithm compared to GA, and find out that HS outperforms GA in speed of test case generation for branch coverage of software code.
format	Thesis
qualification_level	Master's degree
author	Abedinpourshotorban, Hosein
author_facet	Abedinpourshotorban, Hosein
author_sort	Abedinpourshotorban, Hosein
title	Branch coverage test case generation using genetic algorithm and harmony search
title_short	Branch coverage test case generation using genetic algorithm and harmony search
title_full	Branch coverage test case generation using genetic algorithm and harmony search
title_fullStr	Branch coverage test case generation using genetic algorithm and harmony search
title_full_unstemmed	Branch coverage test case generation using genetic algorithm and harmony search
title_sort	branch coverage test case generation using genetic algorithm and harmony search
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2015
url	http://eprints.utm.my/id/eprint/53579/25/HoseinAbedinpourshotorbanMFC2015.pdf
_version_	1747817586443157504

Branch coverage test case generation using genetic algorithm and harmony search

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