# Refactoring Graphs: Assessing Refactoring over Time

arXiv: https://arxiv.org/abs/2003.04666 · HTML: https://mlsanity.com/paper/2003.04666/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Mar 2020.

## Built on by (most cited first, 1 of 1)

- [Refactoring with LLMs: Bridging Human Expertise and Machine Understanding](https://mlsanity.com/paper/2510.03914/) (2025)

## Abstract (arXiv)

Refactoring is an essential activity during software evolution. Frequently, practitioners rely on such transformations to improve source code maintainability and quality. As a consequence, this process may produce new source code entities or change the structure of existing ones. Sometimes, the transformations are atomic, i.e., performed in a single commit. In other cases, they generate sequences of modifications performed over time. To study and reason about refactorings over time, in this paper, we propose a novel concept called refactoring graphs and provide an algorithm to build such graphs. Then, we investigate the history of 10 popular open-source Java-based projects. After eliminating trivial graphs, we characterize a large sample of 1,150 refactoring graphs, providing quantitative data on their size, commits, age, refactoring composition, and developers. We conclude by discussing applications and implications of refactoring graphs, for example, to improve code comprehension, detect refactoring patterns, and support software evolution studies.