Survey on Effective Software Effort Estimation Techniques  

Abstract

Software effort estimation is a very important task in the software engineering field. In this paper gives the overview about the software effort estimation techniques. The techniques are expert estimation, parametric model, algorithmic model, COCOMO, gray relational analysis with genetic algorithm, Ridge Regression (RiR), Multivariate Adaptive Regression Splines (MARS), Robust Regression (RoR), Classification and Regression Tree (CART), Case Based Reasoning (CBR), analogy weights with genetic algorithm are available in the field. And this paper concludes that we cannot say a particular technique is best fit for all the situations to give an accurate estimation. So that we make a careful comparison between all estimation approaches and choose the appropriate technique for each task. It will help us to make accurate software effort estimation by these estimation techniques.  

Authors and Affiliations

Kamalraj. R, , Karthik. S, , Rathi. J

Keywords

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  • EP ID EP141344
  • DOI -
  • Views 92
  • Downloads 0

How To Cite

Kamalraj. R, , Karthik. S, , Rathi. J (2012). Survey on Effective Software Effort Estimation Techniques  . International Journal of Advanced Research in Computer Engineering & Technology(IJARCET), 1(8), 180-183. https://europub.co.uk./articles/-A-141344