Software Metrics for Software Defect Prediction Dataset

<strong>Dataset</strong> used in the article: <em>"Software Source Code Metrics for Software Defects Prediction"*</em> in which we look at the impact of source code level metrics for software defects prediction models in terms of various metrics of prediction performance and the rankings of the metrics. * Dominik Arne Rebro, Bruno Rossi, and Stanislav Chren. 2023. Source Code Metrics for Software Defects Prediction. In Proceedings of ACM SAC Conference (SAC’23). ACM, New York, NY, USA, https://doi.org/10.1145/3555776.3577809 Contents of the package: <strong>dataset/ : </strong>main datasets collected and analyzed in the article <strong>results-rankings-plots/ : </strong>boxplots with the rankings of the metrics for each of the classifiers <strong>Addendum_ProjectsStatistics.png : </strong>table with the mined projects descriptive statistics <strong>Addendum_Acronyms.png</strong> : list of the main software source code metrics acronyms used in the article <strong>Addendum_ThreatsToValidity.png</strong> : main threats to validity that could not be included in the article due to space constraints