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A PSO-based model to increase the accuracy of software development effort estimation

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Abstract

Development effort is one of the most important metrics that must be estimated in order to design the plan of a project. The uncertainty and complexity of software projects make the process of effort estimation difficult and ambiguous. Analogy-based estimation (ABE) is the most common method in this area because it is quite straightforward and practical, relying on comparison between new projects and completed projects to estimate the development effort. Despite many advantages, ABE is unable to produce accurate estimates when the importance level of project features is not the same or the relationship among features is difficult to determine. In such situations, efficient feature weighting can be a solution to improve the performance of ABE. This paper proposes a hybrid estimation model based on a combination of a particle swarm optimization (PSO) algorithm and ABE to increase the accuracy of software development effort estimation. This combination leads to accurate identification of projects that are similar, based on optimizing the performance of the similarity function in ABE. A framework is presented in which the appropriate weights are allocated to project features so that the most accurate estimates are achieved. The suggested model is flexible enough to be used in different datasets including categorical and non-categorical project features. Three real data sets are employed to evaluate the proposed model, and the results are compared with other estimation models. The promising results show that a combination of PSO and ABE could significantly improve the performance of existing estimation models.

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Acknowledgments

We would like to thank the International Software Benchmarking Standards Group (ISBSG) to approve for accessing the ISBSG data set for our research.

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Authors and Affiliations

  1. Department of Software Engineering, University of Technology Malaysia, Skudai, 81310, Johor Bahru, Malaysia

    Vahid Khatibi Bardsiri, Dayang Norhayati Abang Jawawi & Siti Zaiton Mohd Hashim

  2. Department of Computer Engineering, Bardsir Branch, Islamic Azad University, Kerman, Iran

    Elham Khatibi

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  1. Vahid Khatibi Bardsiri
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  2. Dayang Norhayati Abang Jawawi
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Correspondence to Dayang Norhayati Abang Jawawi.

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Khatibi Bardsiri, V., Jawawi, D.N.A., Hashim, S.Z.M. et al. A PSO-based model to increase the accuracy of software development effort estimation. Software Qual J 21, 501–526 (2013). https://doi.org/10.1007/s11219-012-9183-x

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