Abstract: Accurate software cost estimates are critical to both
developers and customers. They can be used for generating request
for proposals, contract negotiations, scheduling, monitoring and
control. The exact relationship between the attributes of the effort
estimation is difficult to establish. A neural network is good at
discovering relationships and pattern in the data. So, in this paper a
comparative analysis among existing Halstead Model, Walston-Felix
Model, Bailey-Basili Model, Doty Model and Neural Network
Based Model is performed. Neural Network has outperformed the
other considered models. Hence, we proposed Neural Network
system as a soft computing approach to model the effort estimation
of the software systems.
Abstract: Various models have been derived by studying large number of completed software projects from various organizations and applications to explore how project sizes mapped into project effort. But, still there is a need to prediction accuracy of the models. As Neuro-fuzzy based system is able to approximate the non-linear function with more precision. So, Neuro-Fuzzy system is used as a soft computing approach to generate model by formulating the relationship based on its training. In this paper, Neuro-Fuzzy technique is used for software estimation modeling of on NASA software project data and performance of the developed models are compared with the Halstead, Walston-Felix, Bailey-Basili and Doty Models mentioned in the literature.