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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
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spelling my.uthm.eprints.8392021-09-06T02:56:43Z http://eprints.uthm.edu.my/839/ Test cases reduction using similarity relation and conditional entropy 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 NonPeerReviewed text en http://eprints.uthm.edu.my/839/1/24p%20NOOR%20FARDZILAWATI%20MD%20NASIR.pdf text en http://eprints.uthm.edu.my/839/2/NOOR%20FARDZILAWATI%20MD%20NASIR%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/839/3/NOOR%20FARDZILAWATI%20MD%20NASIR%20WATERMARK.pdf Md Nasir, Noor Fardzilawati (2017) Test cases reduction using similarity relation and conditional entropy. Masters thesis, Universiti Tun Hussein Onn Malaysia.
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
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
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
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
http://eprints.uthm.edu.my/839/
_version_ 1738580789076951040
score 13.211869

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