Demo Data from EDBT 2026 / reviewers in the wild / expert
Eric S. Liu
dblp:351/7203
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0002-3264-9782ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Software maintenance and evolution · 67% Empirical software engineering · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
mining software repositories |
0.7 | 1 | 2023 | Refactoring in Computational Notebooks · ACM Trans. Softw. Eng. Methodol. 2023 |
Software maintenance and evolution
refactoring |
0.7 | 1 | 2023 | Refactoring in Computational Notebooks · ACM Trans. Softw. Eng. Methodol. 2023 |
Software maintenance and evolution
technical debt |
0.7 | 1 | 2023 | Refactoring in Computational Notebooks · ACM Trans. Softw. Eng. Methodol. 2023 |
Methods — techniques the papers use, named apart from their topics
repository mining · 0.7empirical study · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Refactoring in Computational NotebooksabstractDue to the exploratory nature of computational notebook development, a notebook can be extensively evolved even though it is small, potentially incurring substantial technical debt. Indeed, in interview studies notebook authors have attested to performing ongoing tidying and big cleanups. However, many notebook authors are not trained as software developers, and environments like JupyterLab possess few features to aid notebook maintenance. As software refactoring is traditionally a critical tool for reducing technical debt, we sought to better understand the unique and growing ecology of computational notebooks by investigating the refactoring of public Jupyter notebooks. We randomly selected 15,000 Jupyter notebooks hosted on GitHub and studied 200 with meaningful commit histories. We found that notebook authors do refactor, favoring a few basic classic refactorings as well as those involving the notebook cell construct. Those with a computing background refactored differently than others, but not more so. Exploration-focused notebooks had a unique refactoring profile compared to more exposition-focused notebooks. Authors more often refactored their code as they went along, rather than deferring maintenance to big cleanups. These findings point to refactoring being intrinsic to notebook development. Eric S. Liu, Dylan Lukes, William G. Griswold |
ACM Trans. Softw. Eng. Methodol. | 1 |