Title: Evaluating software cost estimation models using particle swarm optimisation and fuzzy logic for NASA projects: a comparative study

Authors: Alaa F. Sheta, Aladdin Ayesh, David Rine

Addresses: Information Systems Department, College of Computers and Information Systems, Taif University, Haweya 888, Taif, Saudi Arabia. ' Computer Engineering Division, De Montfort University, Leicester, LE1 9BH, UK. ' Computer Science Department, George Mason University, Fairfax, VA 22030, USA

Abstract: Bidding for contracts depends mainly on estimated costs of a given project, which makes an accurate estimation of effort and time required very important with great impact on budget computation and project success. Inaccurate estimates are likely lead to one or all of the following negative outcomes: failure in making a profit, increased probability of incomplete project and delay of project delivery date. In this paper, we provide a comparison between models developed for software cost estimation using particle swarm optimisation (PSO) algorithm, fuzzy logic (FL), and well-known cost estimation models such as Halstead, Walston-Felix, Bailey-Basili and Doty models. The performance of the developed models is evaluated based on the mean magnitude of relative error (MMRE) for NASA software projects.

Keywords: software cost estimation; particle swarm optimisation; PSO; fuzzy logic; Halstead; Walston-Felix; Bailey-Basili; Doty; NASA software projects; contract bidding; modelling; cost models.

DOI: 10.1504/IJBIC.2010.037016

International Journal of Bio-Inspired Computation, 2010 Vol.2 No.6, pp.365 - 373

Published online: 21 Nov 2010 *

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