Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation

Many interaction test data generation strategies (termed t-way strategies) have been developed over the past fifteen years. Despite being very useful, those strategies have assumed sequence-less interaction among the input-values. In this paper, we studied recent works in generating test data for se...

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Main Authors: Kamal Z., Zamli, Mohd Hazli, Mohammed Zabil
Format: Article
Language:English
Published: ICIC International 2013
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/6908/
http://umpir.ump.edu.my/id/eprint/6908/
http://umpir.ump.edu.my/id/eprint/6908/2/ICICIC2012-771-hazli-zamli.PDF
id ump-6908
recordtype eprints
spelling ump-69082018-01-16T00:34:58Z http://umpir.ump.edu.my/id/eprint/6908/ Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation Kamal Z., Zamli Mohd Hazli, Mohammed Zabil Q Science (General) QA76 Computer software Many interaction test data generation strategies (termed t-way strategies) have been developed over the past fifteen years. Despite being very useful, those strategies have assumed sequence-less interaction among the input-values. In this paper, we studied recent works in generating test data for sequence-based t-way. We then proposed a new approach for generating sequence-based t-way, to overcome the unsupported features of the existing strategies as well as to complement the existing sequence-less t-way strategies. Using combinatorial method, our strategy adopted Bees Algorithm (BA) to generate the test data for sequence t-way. Benchmarking results show that our strategy is comparable, and produces better results in some scenarios. BA is the first bio-inspired AI strategy for sequence t-way. ICIC International 2013-03 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6908/2/ICICIC2012-771-hazli-zamli.PDF Kamal Z., Zamli and Mohd Hazli, Mohammed Zabil (2013) Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation. ICIC Express Letters , 7 (3). pp. 929-933. ISSN 1881-803X http://www.ijicic.org/el-7%283%29b.htm
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic Q Science (General)
QA76 Computer software
spellingShingle Q Science (General)
QA76 Computer software
Kamal Z., Zamli
Mohd Hazli, Mohammed Zabil
Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation
description Many interaction test data generation strategies (termed t-way strategies) have been developed over the past fifteen years. Despite being very useful, those strategies have assumed sequence-less interaction among the input-values. In this paper, we studied recent works in generating test data for sequence-based t-way. We then proposed a new approach for generating sequence-based t-way, to overcome the unsupported features of the existing strategies as well as to complement the existing sequence-less t-way strategies. Using combinatorial method, our strategy adopted Bees Algorithm (BA) to generate the test data for sequence t-way. Benchmarking results show that our strategy is comparable, and produces better results in some scenarios. BA is the first bio-inspired AI strategy for sequence t-way.
format Article
author Kamal Z., Zamli
Mohd Hazli, Mohammed Zabil
author_facet Kamal Z., Zamli
Mohd Hazli, Mohammed Zabil
author_sort Kamal Z., Zamli
title Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation
title_short Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation
title_full Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation
title_fullStr Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation
title_full_unstemmed Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation
title_sort adopting bees algorithm for sequenced based t-way test data generation
publisher ICIC International
publishDate 2013
url http://umpir.ump.edu.my/id/eprint/6908/
http://umpir.ump.edu.my/id/eprint/6908/
http://umpir.ump.edu.my/id/eprint/6908/2/ICICIC2012-771-hazli-zamli.PDF
first_indexed 2023-09-18T22:03:05Z
last_indexed 2023-09-18T22:03:05Z
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