Technical debt forecasting: An empirical study on open-source repositories

This dataset contains the static analysis results of 15 open source software applications retrieved from Github, which were used during the TD forecasting process. The results were produced by using SonarQube and CKJM Extended tools. Further details can be found in the relevant publication: Tsoukalas, D., Kehagias, D., Siavvas, M., &amp; Chatzigeorgiou, A. (2020). Technical debt forecasting: an empirical study on open-source repositories. <em>Journal of Systems and Software</em>, <em>170</em>, 110777. More specifically, the dataset includes the following .csv files: <em>_benchmark_repository_measures.csv</em> - the extended dataset that was used for the feature selection process (i.e. descriptive statistics, correlation, univariate and multivariate analysis). Contains TD-related metrics extracted from SonarQube and CKJM Extended <em>15 .csv files</em> that contain TD metrics and measurements of each open-source application, used as input for the TD forecasting models <em>2 anonymised .csv files</em> that contain TD metrics and measurements of the 2 anonymised industrial applications (Project A and Project B), used within the context of the case study