An application of Bayesian network for predicting object-oriented software maintainability
van Koten, Chikako; Gray, Andrew

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van Koten, C., & Gray, A. (2005). An application of Bayesian network for predicting object-oriented software maintainability (Information Science Discussion Papers Series No. 2005/02). University of Otago. Retrieved from http://hdl.handle.net/10523/919
Permanent link to OUR Archive version:
http://hdl.handle.net/10523/919
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.
Date:
2005-03
Publisher:
University of Otago
Pages:
21
Series number:
2005/02
Keywords:
object-oriented systems; maintainability; Bayesian network,
regression tree; regression
Research Type:
Discussion Paper
Notes:
Preprint submitted to Elsevier Science
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- Information Science [486]
- Software Metrics Research Laboratory [22]
- Discussion Paper [439]