A Neuro-Fuzzy Tool for Software Estimation

  • Authors:
  • X. Huang;D. Ho;J. Ren;L. F. Capretz

  • Affiliations:
  • University of Western Ontario;Motorola Canada Ltd.;University of Western Ontario;University of Western Ontario

  • Venue:
  • ICSM '04 Proceedings of the 20th IEEE International Conference on Software Maintenance
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Accurate software estimation such as cost estimation, quality estimation and risk analysis is a major issue in software project management. In this paper, we present a soft computing framework to tackle this challenging problem. We first use a preprocessing neuro-fuzzy inference system to handle the dependencies among contributing factors and decouple the effects of the contributing factors into individuals. Then we use a neuro-fuzzy bank to calibrate the parameters of contributing factors. In order to extend our framework into fields that lack of an appropriate algorithmic model of their own, we propose a default algorithmic model that can be replaced when a better model is available. Validation using industry project data shows that the framework produces good results when used to predict software cost.