Test Doc Submission

Overview This replication package contains all the necessary data and scripts used in our study. The package is structured into four main components. Folder Structure 1. Data processedData: Contains refined datasets that guide our research questions. RawData: Contains raw scraped data about dependents from GitHub, selected for analysis. 2. RepoClonerDataAnalyser The starting repository for the study. Selects the top 10 libraries and their dependents. Clones repositories and conducts analysis for all research questions. Implemented in Python. 3. methodTypeResolutionJavaParser A Java project used for method resolution. After cloning repositories and filtering potential Java files using in RepoClonerDataAnalyzer project, this tool is used for parsing and resolving method types. 4. JacocoCoverageReporter Converts raw JaCoCo HTML coverage reports into CSV format. Implemented in Python Usage Instructions Each project within this package has its own README file with detailed setup and execution instructions. Below is a high-level guide: Data Collection: Use RepoClonerDataAnalyser to select, clone, and filter dependents. Method Resolution: Run methodTypeResolutionJavaParser on filtered Java files. Coverage Analysis: Use JacocoCoverageReporter to convert JaCoCo HTML reports into CSV format and then Use RepoClonerDataAnalyser for further analysis. Please refer our paper for more details. Data Analysis: Utilize the processed data in the Data folder for research insights. Requirements Python 3.x Java 8+ Required dependencies (listed in individual project README files)