An application of Bayesian network for predicting object-oriented software maintainability

  • Authors:
  • C. van Koten;A. R. Gray

  • Affiliations:
  • Department of Information Science, University of Otago, P.O. Box 56, Dunedin 9001, New Zealand;Department of Information Science, University of Otago, P.O. Box 56, Dunedin 9001, New Zealand

  • Venue:
  • Information and Software Technology
  • Year:
  • 2006

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Abstract

As the number of object-oriented software systems increases, it becomes more important for organizations to maintain those systems effectively. However, currently only a small number of maintainability prediction models are available for object-oriented systems. This paper presents a Bayesian network maintainability prediction model for an object-oriented software system. The model is constructed using object-oriented metric data in Li and Henry's datasets, which were collected from two different object-oriented systems. Prediction accuracy of the model is evaluated and compared with commonly used regression-based models. The results suggest that the Bayesian network model can predict maintainability more accurately than the regression-based models for one system, and almost as accurately as the best regression-based model for the other system.