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Journal of Intelligent Systems

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A Novel Hybrid ABC-PSO Algorithm for Effort Estimation of Software Projects Using Agile Methodologies

Thanh Tung Khuat
  • Corresponding author
  • The University of Danang, University of Science and Technology, Danang, Vietnam
  • Email:
/ My Hanh Le
  • The University of Danang, University of Science and Technology, Danang, Vietnam
Published Online: 2017-03-23 | DOI: https://doi.org/10.1515/jisys-2016-0294


In modern software development processes, software effort estimation plays a crucial role. The success or failure of projects depends greatly on the accuracy of effort estimation and schedule results. Many studies focused on proposing novel models to enhance the accuracy of predicted results; however, the question of accurate estimation of effort has been a challenging issue with regards to researchers and practitioners, especially when it comes to projects using agile methodologies. This study aims at introducing a novel formula based on team velocity and story point factors. The parameters of this formula are then optimized by employing swarm optimization algorithms. We also propose an improved algorithm combining the advantages of the artificial bee colony and particle swarm optimization algorithms. The experimental results indicated that our approaches outperformed methods in other studies in terms of the accuracy of predicted results.

Keywords:: Software effort estimation; agile software development; user story; particle swarm optimization; artificial bee colony; swarm optimization algorithm

MSC 2010: 68T20; 68T35; 68N01; 68W25


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About the article

Received: 2016-11-11

Published Online: 2017-03-23

Citation Information: Journal of Intelligent Systems, ISSN (Online) 2191-026X, ISSN (Print) 0334-1860, DOI: https://doi.org/10.1515/jisys-2016-0294.

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