A HYBRID ARTIFICIAL BEE COLONY WITH PARTICLE SWARM OPTIMIZATION FOR MIXED-STRENGTH TEST SUITE GENERATION STRATEGY
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...
| Main Author: | OBAYES, AMMAR KAREEM |
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| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.20715 / |
| Published: |
2021
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| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/20715/1/Ammar%20Kareem%20Obayes%20Alazzawi_16000020.pdf http://utpedia.utp.edu.my/20715/ |
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| Summary: |
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. |
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