EDBT 2026 Demo / reviewers in the wild / expert
Erkai Yu
dblp:426/3940
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved
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 testing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › test coverage
code coverage |
0.9 | 1 | 2025 | DebCovDiff: Differential Testing of Coverage Measurement Tools on Real-World Projects · ASE 2025 |
Software testing
differential testing |
0.9 | 1 | 2025 | DebCovDiff: Differential Testing of Coverage Measurement Tools on Real-World Projects · ASE 2025 |
Software testing
software testing tools |
0.9 | 1 | 2025 | DebCovDiff: Differential Testing of Coverage Measurement Tools on Real-World Projects · ASE 2025 |
Methods — techniques the papers use, named apart from their topics
empirical study · 0.9differential testing · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | DebCovDiff: Differential Testing of Coverage Measurement Tools on Real-World ProjectsabstractMeasuring code coverage is a critical practice in software testing. Incorrect or misleading coverage information reported by automatic tools can increase the software development cost and lead to negative consequences especially for safety-critical software. Ensuring the correctness of coverage measurement tools is therefore important. Prior studies have applied various techniques to find bugs in Gcov and LLVM-cov, the two most widely used coverage tools for C/C++. However, those studies had two limiting factors. First, they used only small, often synthetic, programs, potentially missing bugs in real-world scenarios. Second, they focused only on basic line coverage, neglecting advanced metrics that are both more complex to implement and commonly required for safety-critical software.This paper presents the first empirical study of coverage measurement tools for real-world projects. We implement DebCovDiff, a testing framework that takes Debian packages as the input programs and performs differential testing of Gcov and LLVM-cov, for line coverage and two advanced coverage metrics. We design robust differential oracles to (1) filter out discrepancies arising from subtle differences in the tool output presentation, (2) overcome the nondeterministic nature of certain packages, and (3) support advanced coverage metrics. From results on 47 Debian packages, we identify 34 new bugs, including 2 crashing bugs and 32 deeper bugs that produce wrong coverage reports. Jinghao Jia, Erkai Yu, Darko Marinov, Tianyin Xu |
ASE | 3 |