EDBT 2026 Demo / reviewers in the wild / expert
Yejian Liang
dblp:355/2572
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0000-4443-3711ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 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 |
Empirical software engineering · 50% Software maintenance and evolution · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › software evolution
code evolution |
0.7 | 1 | 2023 | Understanding Solidity Event Logging Practices in the Wild · ESEC/SIGSOFT FSE 2023 |
Empirical software engineering
mining software repositories |
0.7 | 1 | 2023 | Understanding Solidity Event Logging Practices in the Wild · ESEC/SIGSOFT FSE 2023 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Understanding Solidity Event Logging Practices in the WildabstractWriting logging messages is a well-established conventional programming practice, and it is of vital importance for a wide variety of software development activities. The logging mechanism in Solidity programming is enabled by the high-level event feature, but up to now there lacks study for understanding Solidity event logging practices in the wild. To fill this gap, we in this paper provide the first quantitative characteristic study of the current Solidity event logging practices using 2,915 popular Solidity projects hosted on GitHub. The study methodically explores the pervasiveness of event logging, the goodness of current event logging practices, and in particular the reasons for event logging code evolution, and delivers 8 original and important findings. The findings notably include the existence of a large percentage of independent event logging code modifications, and the underlying reasons for different categories of independent event logging code modifications are diverse (for instance, bug fixing and gas saving). We additionally give the implications of our findings, and these implications can enlighten developers, researchers, tool builders, and language designers to improve the event logging practices. To illustrate the potential benefits of our study, we develop a proof-of-concept checker on top of one of our findings and the checker effectively detects problematic event logging code that consumes extra gas in 35 popular GitHub projects and 9 project owners have already confirmed the detected issues. Lantian Li, Yejian Liang, Zhongxing Yu |
ESEC/SIGSOFT FSE | 2 |