Aging-related bugs and software complexity metrics

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Data from authors website

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When What
August 08th, 2015 Donated by Roberto Natella

Reference

Studies who have been using the data (in any form) are required to include the following reference:

@article{cotroneo2013predicting,
  title={Predicting Aging-Related Bugs using Software Complexity Metrics},
  author={Cotroneo, Domenico and Natella, Roberto and Pietrantuono, Roberto},
  journal={Performance Evaluation},
  volume={70},
  number={3},
  pages={163--178},
  year={2013},
  publisher={Elsevier}
}

About the data

This dataset contains information on aging-related bugs found in two open-source projects (the Linux kernel and the MySQL DBMS). This dataset has been used to investigate defect prediction approaches for aging-related bugs, by using software complexity metrics and machine learning techniques. New software complexity metrics were proposed in this study to support defect prediction (“aging-related” metrics).

The dataset contains an ARFF file for each subsystem of the open-source projects. Each row of the ARFF file contains:

  • The name of a file in the project;

  • “Program size” metrics for the file (columns from 2 to 50);

  • “McCabe’s cyclomatic complexity” metrics for the file (columns from 51 to 68);

  • “Halstead” metrics for the file (columns from 69 to 77);

  • “Aging-related” metrics for the file (columns from 78 to 83);

  • The number of aging-related bugs found in the file.