[1] T. M. Khoshgoftaar, N. Seliya,Y. Liu, “Genetic Programming-based Decision Trees for Software Quality Classification,” inProceedings of 15th IEEE International Conference on Tools with Artificial Intelligence, pp. 374-383, IEEE, November 2003 [2] T. Wang and W. H. Li, “Naive Bayes Software Defect Prediction Model,” inProceedings of 2010 International Conference on Computational Intelligence and Software Engineering, pp. 1-4, IEEE, December 2010 [3] D. Gray, D. Bowes, N. Davey, Y. Sun,B. Christianson, “The Misuse of the NASA Metrics Data Program Data Sets for Automated Software Defect Prediction,” inProceedings of 15th Annual Conference on Evaluation & Assessment in Software Engineering (EASE 2011), pp. 96-103, IET., April 2011 [4] V. U. B.Challagulla, F. B. Bastani, I. L. Yen, and R. A. Paul, “Empirical Assessment of Machine Learning based Software Defect Prediction Techniques,” International Journal on Artificial Intelligence Tools, Vol. 17, No. 2, pp. 389-400, 2008 [5] D. Rodriguez, I. Herraiz, R. Harrison, J. Dolado,J. C. Riquelme, “Preliminary Comparison of Techniques for Dealing with Imbalance in Software Defect Prediction,” inProceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering, pp. 43, ACM, May 2014 [6] K. O.Elish and M. O. Elish, “Predicting Defect-Prone Software Modules using Support Vector Machines,” Journal of Systems and Software, Vol. 81, No. 5, pp. 649-660, 2008 [7] Y. Jiang, B. Cuki, T. Menzies,N. Bartlow, “Comparing Design and Code Metrics for Software Quality Prediction,” inProceedings of the 4th International Workshop on Predictor Models in Software Engineering, pp. 11-18, ACM, May 2008 [8] D. Rodriguez, I. Herraiz, R. Harrison, J. Dolado,J. C. Riquelme, “Preliminary Comparison of Techniques for Dealing with Imbalance in Software Defect Prediction,” inProceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering, pp. 43, ACM, May 2014 [9] C. Catal and B. Diri, “Investigating the Effect of Dataset Size, Metrics Sets, and Feature Selection Techniques on Software Fault Prediction Problem,” Information Sciences, Vol. 179, No. 8, pp. 1040-1058, 2009 [10] M. Shepperd, Q. Song, Z. Sun,C. Mair, “Data Quality: Some Comments on the Nasa Software Defect Datasets,” IEEE Transactions on Software Engineering, Vol. 39, No. 9, pp. 1208-1215, 2013 [11] H. S.Shukla and D. K. Verma, “A Review on Software Defect Prediction,” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Vol. 4, No. 12, pp. 4387-4394, 2015 [12] M. Hamill and K. Goseva-Popstojanova, “Exploring Fault Types, Detection Activities, and Failure Severity in an Evolving Safety-Critical Software System,” Software Quality Journal, Vol. 23, No. 2, pp. 229-265, 2015 [13] R. Malhotra, “A Systematic Review of Machine Learning Techniques for Software Fault Prediction,”Applied Soft Computing, Vol. 27, pp. 504-518, 2015 [14] W. Shuo and Y. Xin, “Using Class Imbalance Learning for Software Defect Prediction,” IEEE Transactions on Reliability, Vol. 62, No. 2, pp. 434-443, 2013 [15] A. B. Nassif, M. Azzeh, A. Idri,A. Abran, “Software Development Effort Estimation using Regression Fuzzy Models,”Computational Intelligence and Neuroscience, Vol. 5, 2019 [16] G. Chandrashekar and F. Sahin, ”A Survey on Feature Selection Methods,” Computers & Electrical Engineering, Vol. 40, No. 1, pp. 16-28, 2014 [17] T. Menzies, J. Greenwald,A. Frank, “Data Mining Static Code Attributes to Learn Defect Predictors,” IEEE Transactions on SE, Vol. 33, No. 1, pp. 2-13, 2007 [18] S. Jiang, K. S. Chin, L. Wang, G. Qu,K. L. Tsui, “Modified Genetic Algorithm-based Feature Selection Combined with Pre-Trained Deep Neural Network for Demand Forecasting in Outpatient Department,”Expert Systems with Applications, Vol. 82, pp. 216-230, 2017 [19] D. Gray, D. Bowes, N. Davey, Y. Sun,B. Christianson, “Software Defect Prediction using Static Code Metrics Underestimates Defect-Proneness,” inProceedings of the 2010 International Joint Conference on Neural Networks (IJCNN), pp. 1-7, Barcelona, 2010 [20] P. Refaeilzadeh, L. Tang,H. Liu, “Cross-Validation,” Encyclopedia of Database Systems, Springer, Boston, MA, 2009 |