Test cases reduction using similarity relation and conditional entropy

Testing is essential in software engineering due to the huge size and complexity of everyday software systems. Generation of effective test cases becomes a crucial task due to the increment in the source code size and rapid change of requirements. New test cases are generated and added to a test sui...

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Main Author:	Md Nasir, Noor Fardzilawati
Format:	Thesis
Language:	English English English
Published:	2017
Subjects:	QA76 Computer software
Online Access:	http://eprints.uthm.edu.my/839/1/24p%20NOOR%20FARDZILAWATI%20MD%20NASIR.pdf http://eprints.uthm.edu.my/839/2/NOOR%20FARDZILAWATI%20MD%20NASIR%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/839/3/NOOR%20FARDZILAWATI%20MD%20NASIR%20WATERMARK.pdf
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spelling	my-uthm-ep.8392021-09-06T02:56:43Z Test cases reduction using similarity relation and conditional entropy 2017-12 Md Nasir, Noor Fardzilawati QA76 Computer software Testing is essential in software engineering due to the huge size and complexity of everyday software systems. Generation of effective test cases becomes a crucial task due to the increment in the source code size and rapid change of requirements. New test cases are generated and added to a test suite to exercise the latest modification to software. Therefore, it is not easy to select effective test cases due to their redundancy and having common requirements. Thus, new challenges arise in reducing redundant test cases and finding common requirements that would decrease the cost and maintenance of a software testing process. Given a test suite and a set of requirements covered by test suite, Test Case Reduction or Minimization aims to select a subset of test cases that covers the same requirements. Several techniques have been proposed by researchers based on reduction parameter such as Test Suite Reduction, Fault Capability Detection and Processing Time Reduction. Nonetheless, these techniques are unable to tackle all parameters simultaneously, for example, some techniques may perform well in reducing the size of test cases but less considered on fault detection ability. To address this issue, this study proposed a technique that is able to minimize the size of test cases and common requirement attributes without compromising on fault detection capability. The proposed technique uses Similarity Relation to reduce the size of the test cases and Conditional Entropy to reduce the number of common requirements. The experimental results show a test case reduction that is smaller in size without affecting the decision of the testing. The proposed technique was able to reduce up to 50% of the reduction rate compared to base-line techniques such as MFTS Algorithm, FLOWER, RZOLTAR and Weighted Greedy Algorithm. 2017-12 Thesis http://eprints.uthm.edu.my/839/ http://eprints.uthm.edu.my/839/1/24p%20NOOR%20FARDZILAWATI%20MD%20NASIR.pdf text en public http://eprints.uthm.edu.my/839/2/NOOR%20FARDZILAWATI%20MD%20NASIR%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/839/3/NOOR%20FARDZILAWATI%20MD%20NASIR%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Sains Komputer dan Teknologi Maklumat
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Md Nasir, Noor Fardzilawati Test cases reduction using similarity relation and conditional entropy
description	Testing is essential in software engineering due to the huge size and complexity of everyday software systems. Generation of effective test cases becomes a crucial task due to the increment in the source code size and rapid change of requirements. New test cases are generated and added to a test suite to exercise the latest modification to software. Therefore, it is not easy to select effective test cases due to their redundancy and having common requirements. Thus, new challenges arise in reducing redundant test cases and finding common requirements that would decrease the cost and maintenance of a software testing process. Given a test suite and a set of requirements covered by test suite, Test Case Reduction or Minimization aims to select a subset of test cases that covers the same requirements. Several techniques have been proposed by researchers based on reduction parameter such as Test Suite Reduction, Fault Capability Detection and Processing Time Reduction. Nonetheless, these techniques are unable to tackle all parameters simultaneously, for example, some techniques may perform well in reducing the size of test cases but less considered on fault detection ability. To address this issue, this study proposed a technique that is able to minimize the size of test cases and common requirement attributes without compromising on fault detection capability. The proposed technique uses Similarity Relation to reduce the size of the test cases and Conditional Entropy to reduce the number of common requirements. The experimental results show a test case reduction that is smaller in size without affecting the decision of the testing. The proposed technique was able to reduce up to 50% of the reduction rate compared to base-line techniques such as MFTS Algorithm, FLOWER, RZOLTAR and Weighted Greedy Algorithm.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Md Nasir, Noor Fardzilawati
author_facet	Md Nasir, Noor Fardzilawati
author_sort	Md Nasir, Noor Fardzilawati
title	Test cases reduction using similarity relation and conditional entropy
title_short	Test cases reduction using similarity relation and conditional entropy
title_full	Test cases reduction using similarity relation and conditional entropy
title_fullStr	Test cases reduction using similarity relation and conditional entropy
title_full_unstemmed	Test cases reduction using similarity relation and conditional entropy
title_sort	test cases reduction using similarity relation and conditional entropy
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Komputer dan Teknologi Maklumat
publishDate	2017
url	http://eprints.uthm.edu.my/839/1/24p%20NOOR%20FARDZILAWATI%20MD%20NASIR.pdf http://eprints.uthm.edu.my/839/2/NOOR%20FARDZILAWATI%20MD%20NASIR%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/839/3/NOOR%20FARDZILAWATI%20MD%20NASIR%20WATERMARK.pdf
_version_	1747830690985017344

Test cases reduction using similarity relation and conditional entropy

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