Neural Network and Statistical Modeling of Software Development Effort

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)

Abstract

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.

Keywords

Neural network Software development Effort estimation Regression 

Notes

Acknowledgments

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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Copyright information

© Springer India 2014

Authors and Affiliations

  • Ruchi Shukla
    • 1
  • Mukul Shukla
    • 2
    • 3
  • Tshilidzi Marwala
    • 4
  1. 1.Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburgSouth Africa
  2. 2.Department of Mechanical Engineering TechnologyUniversity of JohannesburgJohannesburgSouth Africa
  3. 3.Department of Mechanical EngineeringMNNITAllahabadIndia
  4. 4.Faulty of Engineering and Built EnvironmentUniversity of JohannesburgJohannesburgSouth Africa

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