Demo Data from EDBT 2026 / reviewers in the wild / expert
Daniel Erhabor
dblp:347/2042
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none
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 |
Empirical software engineering · 50% Program synthesis and code generation · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program synthesis and code generation
code generation with language models |
0.9 | 1 | 2025 | Measuring the Runtime Performance of C++ Code Written by Humans Using Github Copilot · ICSE 2025 |
Empirical software engineering
developer studies |
0.9 | 1 | 2025 | Measuring the Runtime Performance of C++ Code Written by Humans Using Github Copilot · ICSE 2025 |
Methods — techniques the papers use, named apart from their topics
user study · 0.9statistical significance testing · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Measuring the Runtime Performance of C++ Code Written by Humans Using Github CopilotabstractGitHub Copilot is an artificially intelligent programming assistant used by many developers. While a few studies have evaluated the security risks of using Copilot, there has not been any study to show if it aids developers in producing code with better runtime performance. We evaluate the runtime performance of C++ code produced when developers use GitHub Copilot versus when they do not. To this end, we conducted a user study with 32 participants where each participant solved two C++ programming problems, one with Copilot and the other without it and measured the runtime performance of the participants' solutions on our test data. Our results suggest that using Copilot may produce$\mathbf{C + +}$code with (statistically significant) slower runtime performance. Daniel Erhabor, Sreeharsha Udayashankar, Meiyappan Nagappan, Samer Al-Kiswany |
ICSE | 1 |