Comparison and Analysis of Different Software Cost Estimation Methods

Abstract

Software cost estimation is the process of predicting the effort required to develop a software system. 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). Here, the use of support vector regression (SVR) has been proposed for the estimation of software project effort. We have used the COCOMO dataset and our results are compared to Intermediate COCOMO as well as to MOPSO model results for this dataset. It has been observed from the simulation that SVR outperforms other estimating techniques. This paper provides a comparative study on support vector regression (SVR), Intermediate COCOMO and Multiple Objective Particle Swarm Optimization (MOPSO) model for estimation of software project effort. We have analyzed in terms of accuracy and Error rate. Here, data mining tool Weka is used for simulation

Authors and Affiliations

Sweta Kumari , Shashank Pushkar

Keywords

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  • EP ID EP130450
  • DOI 10.14569/IJACSA.2013.040124
  • Views 122
  • Downloads 0

How To Cite

Sweta Kumari, Shashank Pushkar (2013). Comparison and Analysis of Different Software Cost Estimation Methods. International Journal of Advanced Computer Science & Applications, 4(1), 153-157. https://europub.co.uk/articles/-A-130450