Improved Software Fault Prediction using Bayesian Network Classifier
N. Fenton and M. Neil, “Software Metrics: Successes, Failures and New Directions,” J. Systems and Software, vol. 47, nos. 2/3, pp. 149-157, 1999.
Y.Jiang, B. Cukic and T. Menzies, “ Fault Prediction using Early Lifecycle Data”, Proc 18th IEEE Int’l Symp, Software Relaiability, pp. 237-246, 2007.
D. Rodrıguez, R. Ruiz, J. Cuadrado-Gallego, J. Aguilar-Ruiz, M. Garre, “Attribute Selection in Software Engineering Datasets for Detecting Fault Modules”
C. Aliferis, I. Tsamardinos, and A. Statnikov, “HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection,” Proc. AMIA Ann. Symp., 2003.
E. Arisholm and L. Briand, “Predicting Fault-Prone Components in a Java Legacy System,” Proc. ACM/IEEE Int’l Symp. Empirical Software Eng., 2006.
I. Askira-Gelman, “Knowledge Discovery: Comprehensibility of the Results,” Proc. 31st Ann. Hawaii Int’l Conf. System Sciences, vol. 5, pp. 247-256, 1998.
B. Baesens, T. Van Gestel, S. Viaene, M. Stepanova, J. Suykens, and J. Vanthienen, Benchmarking State-of-the-Art Classification Algorithms for Credit Scoring, J. Operational Research Soc., vol. 54, no. 6, pp. 627-635, 2003.
E. Baisch and T. Liedtke, “Comparison of Conventional Approaches and Soft-Computing Approaches for Software Quality Prediction,” Proc. IEEE Int’l Conf. Systems, Man, and Cybernetics, vol. 2, pp. 1045-1049, 1997.
Hall, T. Dept. of Inf. Syst. & Comput., Brunel Univ., Uxbridge, UK Beecham, S. ; Bowes, D. ; Gray, D. ; Counsell, S. “A Systematic Literature Review on Fault Prediction Performance in Software Engineering.
G. Cooper and E. Herskovits, “ A Bayesian Network Method for Induction of Probabilistic Network from Data”, Machine Learning, Vol.9
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