The Full Results and Dataset of Research of Refactoring Volatility

<p>This database is available duplication of the submmitted paper.The details are described below to facilitate replication of the experiment:</p> <ul> <li>Refactoring dataset.zip is a refactoring dataset of 48 projects, stored in json format, including the specific data of 807651 refactoring instances. The shared data can be provided for other research to further expand based on this data.</li> <li>oddsRatioResults.csv is the complete result of RQ1, including odd ratios and p values for 90 refactoring types.</li> <li>Rq2-datacollecting.py is a Python script used in RQ2 to collect different metrics, including metrics for the churn/history/experience dimension.</li> <li>sampling_result.json is a sample data set used in RQ4 to analyze the cause of refactoring volatility.</li> <li>RQ4 - Reasons explaination(Pictures).zip is the specific examples for different reasons for refactoring volatility, including a screenshot of the refactoring code changes at commits.</li> </ul>