Demo Data from EDBT 2026 / reviewers in the wild / expert
Tiago M. Reis
dblp:311/8796
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
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 |
Software maintenance and evolution · 56% Empirical software engineering · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › release engineering
continuous integration |
0.5 | 1 | 2021 | Automatically Deciding on the Integration of Commits Based on Their Descriptions · ASE 2021 |
Empirical software engineering
mining software repositories |
0.5 | 1 | 2021 | Automatically Deciding on the Integration of Commits Based on Their Descriptions · ASE 2021 |
Software maintenance and evolution › software configuration management › software release management
software release |
0.1 | 1 | 2021 | Automatically Deciding on the Integration of Commits Based on Their Descriptions · ASE 2021 |
Methods — techniques the papers use, named apart from their topics
natural language processing · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Automatically Deciding on the Integration of Commits Based on Their DescriptionsabstractContinuous Integration is a critical problem for software maintenance in global projects, compromising companies’ performance, which tends to accumulate a high-resolution time due to the approval process, conflict resolution, tests, and validations. The process of the validation involves the commit description interpretation and can be automated by NLP-mechanisms. This paper presents an intelligent NLP-based approach to evaluate whether the commits can be integrated into a certain software release based only on their descriptions. Our experiments showed an accuracy of 92.9%. Samuel C. Fonseca, Mateus C. Lucena, Tiago M. Reis, Pedro F. Cabral, Walmir A. Silva, Flávia de Souza Santos, Felipe T. Giuntini, Juliano Sales |
ASE | 3 |