Neural Network and Statistical Modeling of Software Development Effort
Many modeling studies that aimed at providing an accurate relationship between the software project effort (or cost) and the involved cost drivers have been conducted for effective management of software projects. However, the derived models are only applicable for a specific project and its variables. In this chapter, we present the use of back-propagation neural network (NN) to model the software development (SD) effort of 18 SD NASA projects based on six cost drivers. The performance of the NN model was also compared with a multi-regression model and other models available in the literature.
KeywordsNeural network Software development Effort estimation Regression
The authors would like to acknowledge the financial support extended by the Faulty of Engineering and Built Environment, University of Johannesburg.
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