Automated Author Profile

Rees-Jones, Mitch

NC State University

Current S-Index

1.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.6

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

78.8%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

2

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Issue Close Time: Datasets + Prediction Classifiers

This project contains experiments on predicting the amount of time required to close issue reports in software repositories. Namely, it contains (a) issue lifetime datasets from 10 large software projects and (b) experiment scripts to generate decision tree classifiers that predict issue close time.To run the cross-validation experiment:
1. Compile the Java classes by running "make" or "make compile-java" on the command line
2. Configure the experimental setup by changing the variables at the top of run.sh
3. Run "bash run.sh" on the command line
4. Results can be found in out/To run the round robin experiment:
1. Compile the Java classes by running "make" or "make compile-java" on the command line
2. Run "bash roundRobin.sh" on the command line
3. Results can be found in out/roundRobin The latest version of this project can be found on GitHub: https://github.com/reesjones/issueCloseTime

Authors

  • Rees-Jones, Mitch ;
  • Martin, Matt ;
  • Menzies, Tim
0 Citations2 Mentions79% FAIR1.6 Dataset Index
10.5281/zenodo.1971112016