A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering

Abstract

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.

Research and Application of Coupled Mechanism and Data-Driven Prediction of Blast Furnace Permeability Index

“…The input parameters are shown in Table 2. Oxygen enrichment X 10 Gas CO 2 volume fraction X 21 Furnace belly gas index X 6 Wind temperature X 11 Gas CO volume fraction…”

“…Big data analytics and intelligent algorithms currently have applications in various fields. Alam Zeb et al [6] applied meta-heuristic algorithms inspired by the collective behaviors of species such as birds, fish, bees, and ants to various areas of software engineering. This study is a guide for researchers to improve the state of the art of current techniques that are commonly used in software engineering with these meta-heuristics.…”

Hybrid Form of Differential Evolutionary and Gray Wolf Algorithm for Multi-AUV Task Allocation in Target Search

“…The wolf optimization algorithm has the characteristics of a fast convergence speed and few parameters. GWO was proposed by Mirjalili et al, scholars from Griffith University, Australia, in 2014 [29], which optimizes the search by simulating the process of gray wolf's predatory prey activities, and it is easy to apply [30]. Singh et al modeled a robot model using an integer-coded wolf pack algorithm, but the proposed assumptions were more idealistic [31].…”