Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation

Structural testing is one of the most important activities within software testing. Ideally, to achieve 100% coverage of every conditions and decisions, tester must take an exhaustive approach. However, exhaustive testing is costly and time consuming. Addressing the aforementioned issues, researcher...

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Main Authors:	Ariful, Haque, Kamal Z., Zamli
Format:	Conference or Workshop Item
Language:	English
Published:	2016
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/14070/ http://umpir.ump.edu.my/id/eprint/14070/1/Comparative%20Analysis%20of%20Neighborhood%20based.pdf

id	ump-14070
recordtype	eprints
spelling	ump-140702018-01-15T07:07:17Z http://umpir.ump.edu.my/id/eprint/14070/ Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation Ariful, Haque Kamal Z., Zamli QA76 Computer software Structural testing is one of the most important activities within software testing. Ideally, to achieve 100% coverage of every conditions and decisions, tester must take an exhaustive approach. However, exhaustive testing is costly and time consuming. Addressing the aforementioned issues, researchers advocate the use of Multiple Condition/Decision Coverage (MC/DC) criteria for sampling of the test cases[1]. Owing the popularity of Search based Software Engineering; many researchers have recently treated MC/DC compliant test case generation as optimization problem. As a result, many meta-heuristic based strategy implementations have appeared in the literature. Most implementations have been focused on neighborhood-based meta-heuristics. In order to help test engineers to make informed decision on the best neighborhood based implementations, this paper investigates the size and time performance of two MC/DC test strategies re-implementation based on Simulated Annealing against two newly developed strategies based on Great Deluge and Late Acceptance Hill Climbing algorithms respectively. Experimental results demonstrate the strength and weakness of the algorithms, change of their behavior on different types of predicates, etc. 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/14070/1/Comparative%20Analysis%20of%20Neighborhood%20based.pdf Ariful, Haque and Kamal Z., Zamli (2016) Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation. In: 3rd International Conference on Communication and Computer Engineering (ICOCOE 2016), 15-17 March 2016 , Bandung, Indonesia. pp. 1-10.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Ariful, Haque Kamal Z., Zamli Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation
description	Structural testing is one of the most important activities within software testing. Ideally, to achieve 100% coverage of every conditions and decisions, tester must take an exhaustive approach. However, exhaustive testing is costly and time consuming. Addressing the aforementioned issues, researchers advocate the use of Multiple Condition/Decision Coverage (MC/DC) criteria for sampling of the test cases[1]. Owing the popularity of Search based Software Engineering; many researchers have recently treated MC/DC compliant test case generation as optimization problem. As a result, many meta-heuristic based strategy implementations have appeared in the literature. Most implementations have been focused on neighborhood-based meta-heuristics. In order to help test engineers to make informed decision on the best neighborhood based implementations, this paper investigates the size and time performance of two MC/DC test strategies re-implementation based on Simulated Annealing against two newly developed strategies based on Great Deluge and Late Acceptance Hill Climbing algorithms respectively. Experimental results demonstrate the strength and weakness of the algorithms, change of their behavior on different types of predicates, etc.
format	Conference or Workshop Item
author	Ariful, Haque Kamal Z., Zamli
author_facet	Ariful, Haque Kamal Z., Zamli
author_sort	Ariful, Haque
title	Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation
title_short	Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation
title_full	Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation
title_fullStr	Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation
title_full_unstemmed	Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation
title_sort	comparative analysis of neighborhood based meta-heuristic algorithms for mc/dc test data generation
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/14070/ http://umpir.ump.edu.my/id/eprint/14070/1/Comparative%20Analysis%20of%20Neighborhood%20based.pdf
first_indexed	2023-09-18T22:17:24Z
last_indexed	2023-09-18T22:17:24Z
_version_	1777415429335023616

Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation

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