This is the dataset that accompanies the study: "Refactoring Debt: Myth or Reality? An Exploratory Study on the Relationship Between Technical Debt and Refactoring." This study has been accepted for publication at the 2022 Mining Software Repositories Conference. Following is the abstract of the study: To meet project timelines or budget constraints, developers intentionally deviate from writing optimal code to feasible code in what is known as incurring \textit{Technical Debt} (TD). Furthermore, as part of planning their correction, developers document these deficiencies as comments in the code (i.e., self-admitted technical debt or SATD). As a means of improving source code quality, developers often apply a series of refactoring operations to their codebase. In this study, we explore developers repaying this debt through refactoring operations by examining occurrences of SATD removal in the code of 76 open-source Java systems. Our findings show that TD payment usually occurs with refactoring activities and developers refactor their code to remove TD for specific reasons. We envision our findings supporting vendors in providing tools to better support developers in the automatic repayment of technical debt.

This study is part of the work conducted by the Source Code Analysis And Natural Language Laboratory. For more information about what we do and to download the preprint of this study, visit: https://scanl.org/