Optimization Algorithm for Prioritizing Software Requirements: A Comparative Study

Software requirement prioritization is a critical step in software development, as it directly impacts project efficiency and success. Despite the availability of various prioritization techniques, there remains a gap in directly comparing optimization algorithms for this purpose. This study address...

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Vydáno v:International Seminar on Research of Information Technology and Intelligent Systems (Online) s. 284 - 289
Hlavní autoři: Naufal Maulana, Moh. Zulfiqar, Siahaan, Daniel, Saikhu, Ahmad, Triandini, Evi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 11.12.2024
Témata:
Accuracy
Comparative Study
Genetic Algorithm
Genetic algorithms
Grey Wolf Optimizer
Optimization
Particle swarm optimization
Resource management
Seminars
Software
Software algorithms
Software development management
Software Requirement Prioritization
Time complexity
ISSN:2832-1456
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Shrnutí:Software requirement prioritization is a critical step in software development, as it directly impacts project efficiency and success. Despite the availability of various prioritization techniques, there remains a gap in directly comparing optimization algorithms for this purpose. This study addresses this gap by evaluating three widely-used metaheuristic-based optimization algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). Using a dataset enriched with attributes such as cost, value, prerequisites, and test cases, the algorithms were analyzed based on accuracy, execution time, and computational complexity. The results show that GA and PSO demonstrate comparable accuracy (82%) and efficiency, with GA exhibiting faster execution time (0.822s) compared to PSO (1.324s). GWO, while slightly less accurate (81%) and slower (3.017s), offers unique advantages in specific optimization contexts. This study provides actionable insights for software engineers in selecting appropriate algorithms to optimize resource allocation and enhance decision-making during requirement prioritization.
ISSN:2832-1456
DOI:10.1109/ISRITI64779.2024.10963649