The comparison of software cost estimation methods using fuzzy sets theory

Abstract

Software cost estimation is a challenging and onerous task. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the categorical data in an explicit and precise manner. Early software estimation models are based on regression analysis or mathematical derivations. Software effort estimation is the process of predicting most realistic use of effort required to develop or maintain software based on incomplete and uncertain input. There are various methods suggested by researchers for calculating effort. The best result are achieved by using soft computing technique. In this paper we have represented size in KLOC as a  triangular fuzzy number. Fuzzy-based methods compare with common methods. MATLAB is used for tuning the parameters of famous various cost estimation methods. On published software projects data, the performance of the method is evaluated. Comparison of results from SCEFL (Software Cost Estimation using Fuzzy Logic) methods with existing ubiquitous methods is done.