Dependency Update Strategies and Package Characteristics

This is the replication package for our paper on predicting dependency update strategies. Here is a short description of what is contained in this package: <strong>Pre-processing Code</strong> The data_preparation.py file filters the initial libraries.io dataset to only include relevant columns for the npm packages. The feature_process.py file includes the majority of preprocessing scripts to derive new features, clean-up missing values and prepare the data for the models. <strong>ML Models</strong> The models.py file contains the scripts for training, validating and evaluating the random forest model and the two baselines (stratified random and SemVer only models) used for the study. <strong>Datasets</strong> The raw dataset can be downloaded from libraries.io. The Processed_Project_Features[SP51][RT].csv dataset is the result of all preprocessing steps and is used in the model feed function. <strong>Visualization Scripts</strong> The visualizer.py file includes the visualization scripts used for the paper.