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SEEPC: A Toolbox for Software Effort Estimation using Soft Computing Techniques

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International Journal of Computer Applications
© 2011 by IJCA Journal
Number 1 - Article 1
Year of Publication: 2011
Authors:
Hari .CH.V.M.K
Tegjyot Singh Sethi
Kaushal .B.S.S
Jagadeesh.M
10.5120/3811-5262

Hari .CH.V.M.K, Tegjyot Singh Sethi and Jagadeesh.M. Article:SEEPC: A Toolbox for Software Effort Estimation using Soft Computing Techniques. International Journal of Computer Applications 31(4):12-19, October 2011. Full text available. BibTeX

@article{key:article,
	author = {Hari .CH.V.M.K and Tegjyot Singh Sethi and Jagadeesh.M},
	title = {Article:SEEPC: A Toolbox for Software Effort Estimation using Soft Computing Techniques},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {31},
	number = {4},
	pages = {12-19},
	month = {October},
	note = {Full text available}
}

Abstract

Software Effort estimation is the process of gauging the amount of effort required to complete the project. With the proliferation of software projects and the heterogeneity in there genre, there is a need for efficient software effort estimation techniques to enable the project managers to perform proper planning of the Software Life Cycle activates. In this article, a new hybrid toolbox based on soft computing techniques for effort estimation is introduced. Particle swarm optimization and cluster analysis has been implemented to perform efficient estimation of effort values with learning ability. The main aim of the toolbox is to provide an efficient, flexible and user friendly way of performing the effort estimation task, by catering to the needs of both the technical and the nontechnical users. The toolbox also implements the COCOMO model to enable a comparative analysis of the proposed model. It was observed that the model when provided with enough training data gave better results when compared with the standard COCOMO values.

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