You can download the archive with the complete experiment results below under attachments.

The archive contains:

• The compiled version of CrossPare used for the execution of the experiments. It has been compiled with the source code of revision [26] in the SVN.
• One folder each of the three data sets. Each folder contains the following:
  • the data
  • the experiment configurations
  • the results as .csv files
• US means only undersampling is applied, i.e., the file contains the configuration/results for ALL data
• US-ENTITYKNN means that undersampling and the KNN data selection is applied, i.e., the file contains the configuration/results for the KNN data selection
• The results contain additional metrics and success measures, we did not discuss in the article, but are evaluated by CrossPare anyways.
  • the metrics error, recall, precision, f-score, g-score, MCC, AUC, AUCec (after Rahman et al.: Recalling the “imprecision” of cross-project defect prediction), true positive rate (tpr), true negative rate (tnr), number of true positives (tp), number of false negatives (fn), number of true negatives (tn), number of false positives (fp)
  • succHe is 1 if recall>0.7 and precision>0.5 (used in the article)
  • succZi is 1 if recall>0.7 and precision>0.7
  • succG75 is 1 if g-score>0.75
  • succG60 is 1 if g-score>0.6
• A batch script for execution the experiments.
  • Be aware the the results are overwritten and the executions will take at quite some time. Moreover, CrossPare will grab all of your CPU cores and consume than too 100%.