A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering
Swarm intelligence algorithms are metaheuristics inspired by the collective behavior of species such as birds, fish, bees, and ants. They are used in many optimization problems due to their simplicity, flexibility, and scalability. These algorithms get the desired convergence during the search by ba...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2023/4577581 |
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| _version_ | 1832548006149226496 |
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| author | Alam Zeb Fakhrud Din Muhammad Fayaz Gulzar Mehmood Kamal Z. Zamli |
| author_facet | Alam Zeb Fakhrud Din Muhammad Fayaz Gulzar Mehmood Kamal Z. Zamli |
| author_sort | Alam Zeb |
| collection | DOAJ |
| description | Swarm intelligence algorithms are metaheuristics inspired by the collective behavior of species such as birds, fish, bees, and ants. They are used in many optimization problems due to their simplicity, flexibility, and scalability. These algorithms get the desired convergence during the search by balancing the exploration and exploitation processes. These metaheuristics have applications in various domains such as global optimization, bioinformatics, power engineering, networking, machine learning, image processing, and environmental applications. This paper presents a systematic literature review (SLR) on applications of four swarm intelligence algorithms i.e., grey wolf optimization (GWO), whale optimization algorithms (WOA), Harris hawks optimizer (HHO), and moth-flame optimizer (MFO) in the field of software engineering. It presents an in-depth study of these metaheuristics’ adoption in the field of software engineering. This SLR is mainly comprised of three phases such as planning, conducting, and reporting. This study covers all related studies published from 2014 up to 2022. The study shows that applications of the selected metaheuristics have been utilized in various fields of software engineering especially software testing, software defect prediction, and software reliability. The study also points out some of the areas where applications of these swarm intelligence algorithms can be utilized. This study may act as a guideline for researchers in improving the current state-of-the-art on generally adopting these metaheuristics in software engineering. |
| format | Article |
| id | doaj-art-ac600c6a46904323947532370173ba07 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-ac600c6a46904323947532370173ba072025-02-03T06:42:38ZengWileyComplexity1099-05262023-01-01202310.1155/2023/4577581A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software EngineeringAlam Zeb0Fakhrud Din1Muhammad Fayaz2Gulzar Mehmood3Kamal Z. Zamli4Faculty of Information TechnologyFaculty of Information TechnologyDepartment of Computer ScienceDepartment of Computer ScienceFaculty of Science and TechnologySwarm intelligence algorithms are metaheuristics inspired by the collective behavior of species such as birds, fish, bees, and ants. They are used in many optimization problems due to their simplicity, flexibility, and scalability. These algorithms get the desired convergence during the search by balancing the exploration and exploitation processes. These metaheuristics have applications in various domains such as global optimization, bioinformatics, power engineering, networking, machine learning, image processing, and environmental applications. This paper presents a systematic literature review (SLR) on applications of four swarm intelligence algorithms i.e., grey wolf optimization (GWO), whale optimization algorithms (WOA), Harris hawks optimizer (HHO), and moth-flame optimizer (MFO) in the field of software engineering. It presents an in-depth study of these metaheuristics’ adoption in the field of software engineering. This SLR is mainly comprised of three phases such as planning, conducting, and reporting. This study covers all related studies published from 2014 up to 2022. The study shows that applications of the selected metaheuristics have been utilized in various fields of software engineering especially software testing, software defect prediction, and software reliability. The study also points out some of the areas where applications of these swarm intelligence algorithms can be utilized. This study may act as a guideline for researchers in improving the current state-of-the-art on generally adopting these metaheuristics in software engineering.http://dx.doi.org/10.1155/2023/4577581 |
| spellingShingle | Alam Zeb Fakhrud Din Muhammad Fayaz Gulzar Mehmood Kamal Z. Zamli A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering Complexity |
| title | A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering |
| title_full | A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering |
| title_fullStr | A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering |
| title_full_unstemmed | A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering |
| title_short | A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering |
| title_sort | systematic literature review on robust swarm intelligence algorithms in search based software engineering |
| url | http://dx.doi.org/10.1155/2023/4577581 |
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