To cite package 'reproducer' in publications please use:

Madeyski L, Jureczko M (2015). “Which process metrics can significantly improve defect prediction models? An empirical study.” Software Quality Journal, 23(3), 393–422. doi:10.1007/s11219-014-9241-7, https://dx.doi.org/10.1007/s11219-014-9241-7.

Jureczko M, Madeyski L (2015). “Cross-project defect prediction with respect to code ownership model: An empirical study.” e-Informatica Software Engineering Journal, 9(1), 21–35. doi:10.5277/e-Inf150102, https://dx.doi.org/10.5277/e-Inf150102.

Kitchenham B, Madeyski L, Budgen D, Keung J, Brereton P, Charters S, Gibbs S, Pohthong A (2017). “Robust Statistical Methods for Empirical Software Engineering.” Empirical Software Engineering, 22(2), 579–630. doi:10.1007/s10664-016-9437-5, https://dx.doi.org/10.1007/s10664-016-9437-5.

Madeyski L, Kitchenham B (2018). “Effect Sizes and their Variance for AB/BA Crossover Design Studies.” Empirical Software Engineering, 23(4), 1982–2017. doi:10.1007/s10664-017-9574-5, https://doi.org/10.1007/s10664-017-9574-5.

Kitchenham B, Madeyski L, Pearl P (2020). “Meta-analysis for families of experiments in software engineering: a systematic review and reproducibility and validity assessment.” Empirical Software Engineering, 25(1), 353–401. doi:10.1007/s10664-019-09747-0, https://doi.org/10.1007/s10664-019-09747-0.

Lewowski T, Madeyski L (2020). “Creating Evolving Project Data Sets in Software Engineering.” In Jarzabek S, Poniszewska-Mara'nda A, Madeyski L (eds.), Integrating Research and Practice in Software Engineering, volume 851 series Studies in Computational Intelligence, chapter Creating Evolving Project Data Sets in Software Engineering, 1–14. Springer. doi:10.1007/978-3-030-26574-8_1, https://doi.org/10.1007/978-3-030-26574-8_1.

Kitchenham B, Madeyski L, Scanniello G, Gravino C (2022). “The importance of the correlation in crossover experiments.” IEEE Transactions on Software Engineering, 48(8), 2802–2813. doi:10.1109/TSE.2021.3070480, https://doi.org/10.1109/TSE.2021.3070480.

Madeyski L (2023). reproducer: Reproduce Statistical Analyses and Meta-Analyses. R package version 0.5.3, https://madeyski.e-informatyka.pl/reproducible-research/.

Corresponding BibTeX entries:

  @Article{,
    title = {Which process metrics can significantly improve defect
      prediction models? An empirical study},
    author = {Lech Madeyski and Marian Jureczko},
    journal = {Software Quality Journal},
    year = {2015},
    volume = {23},
    number = {3},
    pages = {393--422},
    doi = {10.1007/s11219-014-9241-7},
    url = {https://dx.doi.org/10.1007/s11219-014-9241-7},
  }

  @Article{,
    title = {Cross-project defect prediction with respect to code
      ownership model: An empirical study},
    author = {Marian Jureczko and Lech Madeyski},
    journal = {e-Informatica Software Engineering Journal},
    year = {2015},
    volume = {9},
    number = {1},
    pages = {21--35},
    doi = {10.5277/e-Inf150102},
    url = {https://dx.doi.org/10.5277/e-Inf150102},
  }

  @Article{,
    title = {Robust Statistical Methods for Empirical Software
      Engineering},
    author = {Barbara Kitchenham and Lech Madeyski and David Budgen and
      Jacky Keung and Pearl Brereton and Stuart Charters and Shirley
      Gibbs and Amnart Pohthong},
    journal = {Empirical Software Engineering},
    year = {2017},
    volume = {22},
    number = {2},
    pages = {579--630},
    doi = {10.1007/s10664-016-9437-5},
    url = {https://dx.doi.org/10.1007/s10664-016-9437-5},
  }

  @Article{,
    title = {Effect Sizes and their Variance for AB/BA Crossover Design
      Studies},
    author = {Lech Madeyski and Barbara Kitchenham},
    journal = {Empirical Software Engineering},
    year = {2018},
    volume = {23},
    number = {4},
    pages = {1982--2017},
    doi = {10.1007/s10664-017-9574-5},
    url = {https://doi.org/10.1007/s10664-017-9574-5},
  }

  @Article{,
    title = {Meta-analysis for families of experiments in software
      engineering: a systematic review and reproducibility and validity
      assessment},
    author = {Barbara Kitchenham and Lech Madeyski and Pearl Pearl},
    journal = {Empirical Software Engineering},
    year = {2020},
    volume = {25},
    number = {1},
    pages = {353--401},
    doi = {10.1007/s10664-019-09747-0},
    url = {https://doi.org/10.1007/s10664-019-09747-0},
  }

  @InBook{,
    title = {Creating Evolving Project Data Sets in Software
      Engineering},
    booktitle = {Integrating Research and Practice in Software
      Engineering},
    chapter = {Creating Evolving Project Data Sets in Software
      Engineering},
    author = {Tomasz Lewowski and Lech Madeyski},
    editor = {Stanislaw Jarzabek and Aneta Poniszewska-Mara{'{n}}da and
      Lech Madeyski},
    year = {2020},
    volume = {851},
    series = {Studies in Computational Intelligence},
    pages = {1--14},
    publisher = {Springer},
    doi = {10.1007/978-3-030-26574-8_1},
    url = {https://doi.org/10.1007/978-3-030-26574-8_1},
  }

  @Article{,
    title = {The importance of the correlation in crossover
      experiments},
    author = {Barbara Kitchenham and Lech Madeyski and Giuseppe
      Scanniello and Carmine Gravino},
    journal = {IEEE Transactions on Software Engineering},
    year = {2022},
    volume = {48},
    number = {8},
    pages = {2802--2813},
    doi = {10.1109/TSE.2021.3070480},
    url = {https://doi.org/10.1109/TSE.2021.3070480},
  }

  @Manual{,
    title = {reproducer: Reproduce Statistical Analyses and
      Meta-Analyses},
    author = {Lech Madeyski},
    year = {2023},
    note = {R package version 0.5.3},
    url = {https://madeyski.e-informatyka.pl/reproducible-research/},
  }