Optimised class point approach for software effort estimation using adaptive neuro-fuzzy inference system model

AbstractThe success of software development depends very much on proper estimation of effort required to develop the software. There is no simple way to make an accurate estimate of these parameters required to develop a software system. There are basically some points approach which are available for software effort estimation such as function point, use case point, class point, object point, etc. In this paper, our aim is to estimate the cost of various software projects using class point approach. The parameters are optimised using various soft computing techniques such as fuzzy logic and adaptive neuro-fuzzy logic so as to achieve better accuracy. Also, a comparative analysis of software effort estimation using the techniques such as artificial neural network ANN, fuzzy logic FL and adaptive neuro-fuzzy inference system ANFIS has been provided.