The proceedings contain 6 papers. The topics discussed include: using source code metrics to predict change-prone web services: a case-study on eBay services; investigating code smell co-occurrences using association rule learning: a replicated study; using machine learning to design a flexible LOC counter; machine learning for finding bugs: an initial report; automatic feature selection by regularization to improve bug prediction accuracy; and hyperparameter optimization to improve bug prediction accuracy.
ARCELLI FONTANA, F., Walter, B., Zanoni, M. (2017). IEEE International Workshop on Machine Learning Techniques for Software Quality Evaluation. In IEEE International Workshop on Machine Learning Techniques for Software Quality Evaluation. Institute of Electrical and Electronics Engineers Inc..
IEEE International Workshop on Machine Learning Techniques for Software Quality Evaluation
ARCELLI FONTANA, FRANCESCA;ZANONI, MARCO
2017
Abstract
The proceedings contain 6 papers. The topics discussed include: using source code metrics to predict change-prone web services: a case-study on eBay services; investigating code smell co-occurrences using association rule learning: a replicated study; using machine learning to design a flexible LOC counter; machine learning for finding bugs: an initial report; automatic feature selection by regularization to improve bug prediction accuracy; and hyperparameter optimization to improve bug prediction accuracy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.