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SOFTWARE COST ESTIMATION USING FUZZY NUMBER AND PARTICLE SWARM OPTIMIZATION

Authors

Divya Kashyap1 and D. L. Gupta2
1Computer Science and Engineering Department, IADC, Bangalore 2Computer Science and Engineering Department, KNIT, Sultanpur

Abstract

Software cost estimation is a process to calculate effort, time and cost of a project, and assist in better decision making about the feasibility or viability of project. Accurate cost prediction is required to effectively organize the project development tasks and to make economical and strategic planning, project management. There are several known and unknown factors affect this process, so cost estimation is a very difficult process. Software size is a very important factor that impacts the process of cost estimation. Accuracy of cost estimation is directly proportional to the accuracy of the size estimation. Failure of Software projects has always been an important area of focus for the Software Industry. Implementation phase is not the only phase for Software projects to fail, instead planning and estimation steps are the most crucial ones, which lead to their failure. More than 50% of the total projects fail which go beyond the estimated time and cost. The Standish group‘s CHAOS reports failure rate of 70% for the software projects. This paper presents the existing algorithms for software estimation and the relevant concepts of Fuzzy Theory and PSO. Also explains the proposed algorithm with experimental results.

Keywords

Software Cost estimation, Particle swarm optimization, Fuzzy logic etc