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Multi Objective Particle Swarm Optimization for Software Cost Estimation

  • G. Sivanageswara Rao
  • Ch. V. Phani Krishna
  • K. Rajasekhara Rao
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 248)

Abstract

Planning, monitoring-control and termination activities are classified as Software Project Management. The most vital activity in project management is planning which states the resources required to complete the project successfully. To complete the project successfully Software Cost Estimation is very important. Software Cost Estimation is the process of predicting the cost and time required. The basic input for the software cost estimation is coding size and set of cost drivers, the output is Effort in terms of Person-Months (PM’s). In this paper, we have proposed a model for tuning parameters of COCOMO model Software Cost Estimation using Multi Objective (MO) Particle Swarm Optimization. The parameters of model tuned by using MOPSO considering two objectives Mean Absolute Relative Error and Prediction. The dataset COCOMO is considered for testing the model. It was observed that the model we proposed gives better results when compared with the standard COCOMO model. It is also observed, when provided with enough classification among training data may give better results.

Keywords

KDLOC-thousands of delivered lines of code PM- person months PSO- particle swarm optimization COCOMO- constructive cost estimation MO- Multi Objective 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • G. Sivanageswara Rao
    • 1
  • Ch. V. Phani Krishna
    • 1
  • K. Rajasekhara Rao
    • 1
  1. 1.Department of Computer Science & EngineeringKL UniversityGunturIndia

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