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A HYBRID ARTIFICIAL BEE COLONY WITH PARTICLE SWARM OPTIMIZATION FOR MIXED-STRENGTH TEST SUITE GENERATION STRATEGY

OBAYES, AMMAR KAREEM (2021) A HYBRID ARTIFICIAL BEE COLONY WITH PARTICLE SWARM OPTIMIZATION FOR MIXED-STRENGTH TEST SUITE GENERATION STRATEGY. PhD thesis, Universiti Teknologi PETRONAS.

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Abstract

Software testing is essential part of software development life cycle. Yet, exhaustive testing of highly configurable software is impractical owing to the limited time and resources. Furthermore, exhaustive testing leads to a combinatorial explosion problem whereby the test cases grow exponentially with the increase of software inputs. Owing to its effectiveness for bug finding, many researchers are turning to the sampling strategies based on input interaction, called t-way testing, where t indicates the interaction strength. Known to be an NP-hard (i.e. Non-deterministic Polynomial-time) problem, the process of minimizing t-way test cases is challenging owing to the potentially large generated search space when dealing with large input values. To date, many t-way strategies have been proposed in the literature.

Item Type: Thesis (PhD)
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 08 Sep 2021 12:07
Last Modified: 08 Sep 2021 12:07
URI: http://utpedia.utp.edu.my/id/eprint/20715

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