SOFTWARE DEVELOPMENT EFFORT ESTIMATION USING SOFT COMPUTING METHODS

Effort estimation of software development is a daunting work that is being carried out by software developers as not much of the data about the software which is to be developed is available during the early stages of software development) are fuzzified that leads to reliable and accurate estimation of effort. The results show that the value of Magnitude of Relative Error (MRE) obtained by applying fuzzy logic is quite lower than MRE obtained from algorithmic model. By analyzing the results further it is observed that Gaussian Membership Function performs better than Triangular Membership Function and Trapezoidal Membership Function as the transition from one interval to another is quite smoother. Here varying number of COCOMO II inputs are fuzzified with these membership functions. The main reason for this issue is imprecision of the estimation. In this paper, several existing methods for software effort estimation are illustrated and their aspects will be discussed. Comparing the features of the methods could be applied for clustering based abilities; it is also useful for selecting the special method for each of the projects. The history of using each estimation model leads to have a good choice for an especial software project. In this paper an example of software cost estimation is also presented in an actual software project.