Abstract
AbstractSoftware is everywhere. Now-a-day’ s software plays an indispensable role in all the fields like Education, Medical, Insurance, Marketing, Stock Exchange etc. The major goal of software organization is to achieve the Win-Win condition. As per the Standish Group Chaos Survey, only 30–40% of the software projects are successful. One of the main reasons for failure of the software projects is inaccurate estimations of the cost and schedule. In the conventional software development Algorithmic and Expert Based techniques are used to predict the effort, duration and cost of the software project. But they are not providing accurate estimations of the software effort. Most recently, the industries and researchers are adopting Soft Computing techniques to estimate the software effort accurately in the early stage of software development. In this chapter, the Soft Computing techniques for effort estimation using Fuzzy Logic, Neural Networks (NN), Adaptive Neuro Fuzzy Inference System (ANFIS), Random Forest and Support Vector Machines (SVM) are introduced. Soft Computing models are developed using Fuzzy Logic, Neural Networks and ANFIS using the NASA93 and Desharnais Datasets. Comparing these models using different evaluation criteria, it is observed that the Adaptive Neuro Fuzzy Inference System produced better effort estimates.
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