Towards identifying software project clusters with regard to defect prediction

By Marian Jureczko, Lech Madeyski. International Conference on Predictive Models in Software Engineering, 2010

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The Impact of Automated Parameter Optimization on Defect Prediction Models (2018, unknown): “[67].”
Automated Parameter Optimization of Classification Techniques for Defect Prediction Models (2016, unknown): “[24].”
An empirical study on software defect prediction with a simplified metric set (2014, methodology): “All the data sets were collected by Jureczko and Madeyski [11], and Jureczko and Spinellis [12] with the help of two existing tools (BugInfo and Ckjm).”
An investigation on the feasibility of cross-project defect prediction (2011, methodology): “However, in practice, such kind of historical data is not always available, because either it does not yet exist or was not well collected (Zimmermann et al. 2009; Turhan et al. 2009; Jureczko and Madeyski 2010).”
Software Defect Prediction via Convolutional Neural Network (2017, methodology): “The 20 traditional features are carefully extracted by Jureczko et al., the dataset contributors [26].”
An Empirical Comparison of Model Validation Techniques for Defect Prediction Models (2017, unknown): “[52].”