VLDB 2026 Research / reviewers in the wild / expert
Gabriel Silva de Oliveira
dblp:257/1084
· DBLP profile ↗
4ranked-venue papers
1as first author
4since 2021 · last 2025
0009-0008-7817-3928ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 3 · 1 first-author · 3 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | EclipseMonitor: A Real-Time Student Programming Environment Data Collection ToolabstractFigure 1: EclipseMonitor workflow diagram.It shows how the student's coding session data from Eclipse development environment has been collected through the EclipseMonitor. Saminur Islam, Zhikai Gao, John Bacher, Gabriel Silva de Oliveira, Varad Patwardhan, Sarah Smith Heckman, Collin F. Lynch |
SIGCSE (2) | 4 |
| 2024 | Who Should I Help Next? Simulation of Office Hours Queue Scheduling Strategy in a CS2 Course
Zhikai Gao, Gabriel Silva de Oliveira, Damilola Babalola, Collin F. Lynch, Sarah Smith Heckman |
EDM | 2 |
| 2024 | Using Survival Analysis to Model Students' Patience in Online Office Hour QueuesabstractPromptly and properly addressing students' help requests during office hours is a critical challenge for large CS courses. With a large number of help requests, the queue gets longer and students have to endure long wait times. To address this problem, we try to quantify students' patience in the queue through survival analysis. Our results show that half of the students are willing to stay in the queue after waiting for 142.5 minutes. Moreover, we find that female students, morning requests, returning students, and requests about test failures are more likely to stay in the queue for a longer time. Zhikai Gao, Adam M. Gaweda, Collin F. Lynch, Sarah Smith Heckman, Damilola Babalola, Gabriel Silva de Oliveira |
SIGCSE (2) | 6 |
| 2024 | Exploring Novice Programmers' Testing Behavior: A First Step to Define Coding StruggleabstractTo promote good coding practices, we need to understand what students do when they are on their own. In this research study, we explore students' testing behavior and response to persistent errors to better understand their coding patterns. We investigate how those patterns change when they struggle, and how help-seeking might influence their coding behaviors. We define struggle during coding as failing the same unit test case consecutively for more than four submission events, considering only unit test cases created by the instructors. To analyze the students' coding data, we use progress indicators, student test implementation indicators, and both student-generated and instructor-generated unit test results from each student submission event. In addition, we use office hours attendance records and amount of assignment-related posts created on the course forum. Results show that students tend not to follow test-driven development practices, even when explicitly directed to, and tend to create unit tests only to earn assignment credit rather than to guide their software development. Students also tend not to modify their own unit tests once they have earned the related credits, even when facing coding struggle; they tend to modify their unit tests only after they have been facing coding struggle for an extended number of submission events. Gabriel Silva de Oliveira, Zhikai Gao, Sarah Smith Heckman, Collin F. Lynch |
SIGCSE (1) | 1 |