Toward Better Understanding and Documentation of Rationale for Code Changes

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Virginia Tech


Software development is driven by the development team's decisions. Communicating the rationale behind these decisions is essential for the projects success. Although the software engineering community recognizes the need and importance of rationale, there has been a lack of in-depth study of rationale for code changes. To bridge this gap, this dissertation examines the rationale behind code changes in-depth and breadth. This work includes two studies and an experiment. The first study aims to understand software developers' need. It finds that software developers need to investigate code changes to understand their rationale when working on diverse tasks. The study also reveals that software developers decompose the rationale of code commits into 15 separate components that they could seek when searching for rationale. The second study surveys software developers' experiences with rationale. It uncovers issues and challenges that software developers encounter while searching for and recording rationale for code changes. The study highlights rationale components that are needed and hard to find. Additionally, it discusses factors leading software developers to give up their search for the rationale of code changes. Finally, the experiment predicts the documentation of rationale components in pull request templates. Multiple statistical models are built to predict if rationale components' headers will not be filled. The trained models are effective in achieving high accuracy and recall. Overall, this work's findings shed light on the need for rationale and offer deep insights for fulfilling this important information need.



Software Engineering, Software Evolution and Maintenance, Revision Control Systems, Software Changes Rationale, Applied Machine Learning.