Estimation of project success using Bayesian classifier

  • Authors:

  • Seiya Abe;Osamu Mizuno;Tohru Kikuno;Nahomi Kikuchi;Masayuki Hirayama

  • Affiliations:

  • Osaka University, Osaka, Japan;Osaka University, Osaka, Japan;Osaka University, Osaka, Japan;Information-technology Promotion Agency, Tokyo, Japan;Information-technology Promotion Agency, Tokyo, Japan

  • Venue:
  • Proceedings of the 28th international conference on Software engineering
  • Year:
  • 2006

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Abstract

The software projects are considered to be successful if the cost and the duration are within the estimated ones and the quality is satisfactory. To attain project success, the project management, in which the final status of project is estimated, must be incorporated.In this paper, we consider estimation of the final status(that is, successful or unsuccessful) of project by applying Bayesian classifier to metrics data collected from project. In order to attain high estimation accuracy rate, we must select only a set of appropriate metrics to be applied. Here we consider two selection methods: the first method by the experts and the second method by the statistical test.Then we conducted an experiment using 28 project data and 29 metrics data in an organization of a certain company. The result showed that the method by the test gave higher accuracy rates than the method by the experts, and Bayesian classifier with the test method is effective to estimate project success.