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Particle Swarm Optimization in the fine-tuning of Fuzzy Software Cost Estimation Models

Prasad Reddy P.V.G.D

Pages - 12 - 23 | Revised - 30-06-2010 | Published - 10-08-2010

Published in International Journal of Software Engineering (IJSE)

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KEYWORDS

Particle Swarm Optimization Algorithm (PSOA), , Fuzzy Estimate,, software cost estimation, Effort Estimation,

ABSTRACT

Software cost estimation deals with the financial and strategic planning of software projects. Controlling the expensive investment of software development effectively is of paramount importance. The limitation of algorithmic effort prediction models is their inability to cope with uncertainties and imprecision surrounding software projects at the early development stage. More recently, attention has turned to a variety of machine learning methods, and soft computing in particular to predict software development effort. Fuzzy logic is one such technique which can cope with uncertainties. In the present paper, Particle Swarm Optimization Algorithm (PSOA) is presented to fine tune the fuzzy estimate for the development of software projects . The efficacy of the developed models is tested on 10 NASA software projects, 18 NASA projects and COCOMO 81 database on the basis of various criterion for assessment of software cost estimation models. Comparison of all the models is done and it is found that the developed models provide better estimation

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Professor Prasad Reddy P.V.G.D

Andhra University - India

prasadreddypvgd@gmail.com