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Predicting Software Fault Proneness Model Using Neural Network.

, , and . XP, volume 9 of Lecture Notes in Business Information Processing, page 215-217. Springer, (2008)

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An Empirical Study of Robustness and Stability of Machine Learning Classifiers in Software Defect Prediction., and . ISI (1), volume 320 of Advances in Intelligent Systems and Computing, page 383-397. Springer, (2014)Software Reuse Metrics for Object-Oriented Systems., , , and . SERA, page 48-55. IEEE Computer Society, (2005)Technique for Detecting Early-Warning Signals of Performance Deterioration in Large Scale Software Systems., and . ICPE, page 213-222. ACM, (2017)Some Interoperability Issues in the Designing of Web Services : Case Study on Credit Card, and . International Journal on Web Service Computing (IJWSC), 4 (4): 13 (December 2013)Interoperability issues in Web Services., and . CCSEIT, page 614-619. ACM, (2012)Heterogeneous Fault Prediction Using Feature Selection and Supervised Learning Algorithms., and . Vietnam. J. Comput. Sci., 9 (3): 261-284 (2022)A Novel Four-Way Approach Designed With Ensemble Feature Selection for Code Smell Detection., and . IEEE Access, (2021)Fault coverage-based test suite optimization method for regression testing: learning from mistakes-based approach., , , and . Neural Comput. Appl., 32 (12): 7769-7784 (2020)An empirical evaluation of classification algorithms for fault prediction in open source projects., and . J. King Saud Univ. Comput. Inf. Sci., 30 (1): 2-17 (2018)Grey relational effort analysis technique using regression methods for software estimation., , and . Int. Arab J. Inf. Technol., 11 (5): 437-446 (2014)