Program

9.00 Introduction and presentation of speakers

Session I (chair: Francesca Arcelli Fontana)

  • 09.20 Lov Kumar, Santanu Rath and Ashish Sureka: Using Source Code Metrics to Predict Change-Prone Web Services - A Case-Study on eBay Services. [youtube]
  • 09.40 Fabio Palomba, Rocco Oliveto and Andrea De Lucia: Investigating Code Smell Co-Occurrences using Association Rule Learning: A Replicated Study.
  • 10.00 Mirosław Ochodek, Miroslaw Staron, Dominik Bargowski, Wilhelm Meding and Regina Hebig: Using Machine Learning to Design a Flexible LOC. [slides]
  • 10.20 short discussion on the previous presentations
11.30 Coffee break

Session II (chair: Bartosz Walter)

  • 11.00 Timothy Chappell, Cristina Cifuentes, Paddy Krishnan and Shlomo Geva: Machine Learning For Finding Bugs: An Initial Report. [slides]
  • 11.20 Haidar Osman, Mohammad Ghafari and Oscar Nierstrasz: Automatic Feature Selection by Regularization to Improve Bug Prediction Accuracy. [slides]
  • 11.40 Haidar Osman, Mohammad Ghafari and Oscar Nierstrasz: Hyperparameter Optimization to Improve Bug Prediction Accuracy. [slides]
  • 12.00 conclusions and next steps
12.30 Lunch