(untitled) (International Journal of Engineering and Computer Science, 2015)
Many risks are involved in the development of software project and Risk assessment methods are most important component in the process of risk management. They are a critical component of software project management and software testing. Practitioners, particularly researchers, are mostly interested in the evaluation of these methods for their applicability, strengths, and weaknesses for particular scenarios. So far, no model has proved to be successful at effectively and consistently predicting software development cost. Fuzzy Ex-COM (Fuzzy Expert COCOMO) that combines the advantages of a fuzzy technique with Expert COCOMO methodology for risk assessment in a software project which leverages existing knowledge and expertise from previous effort estimation activities to assess the risk in a new software project. A novel Neuro-fuzzy Expert Constructive Cost Model is proposed to improve the accuracy of risk assessment technique. With the introduction of the Neuro-Fuzzy Risk Methodology which combines the non-linear learning features of neural networks with fuzzy logic that has capability to deal with sensitive and linguistic data and generate risk rules using Artificial Neural Network(ANN) techniques to improve the accuracy of risk assessment technique. This paper shows the workflow required for implementing the Neuro-Fuzzy Risk Methodology on the original Fuzzy Ex-COCOMO methodology.