Demo Data from EDBT 2026 / reviewers in the wild / expert
Sheng Zhan
dblp:190/1159
· DBLP profile ↗
3ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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 |
Program analysis · 56% Concurrent programming · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Concurrent programming › concurrency bug detection
data race detection |
0.2 | 1 | 2016 | ECHO: instantaneous in situ race detection in the IDE · SIGSOFT FSE 2016 |
Program analysis › concurrent program analysis
static race detection |
0.2 | 1 | 2016 | ECHO: instantaneous in situ race detection in the IDE · SIGSOFT FSE 2016 |
Program analysis
static analysis |
0.1 | 1 | 2016 | ECHO: instantaneous in situ race detection in the IDE · SIGSOFT FSE 2016 |
Methods — techniques the papers use, named apart from their topics
happens-before graph · 0.2change-aware analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Fast-colorfool: faster and more transferable semantic adversarial attack with complementary colors and cumulative perturbation
Xueqiang Han, Zhiguo Cui, Sheng Zhan, Qing Tian 0003 |
Multim. Syst. | 4 |
| 2024 | Innovative multi-stage matching for counting anything
Sheng Zhan, Zhiguo Cui, Feiyu Li |
Pattern Recognit. Lett. | 3 |
| 2016 | ECHO: instantaneous in situ race detection in the IDEabstractWe present ECHO, a new technique that detects data races instantaneously in the IDE while developers code. ECHO is the first technique of its kind for incremental race detection supporting both code addition and deletion in the IDE. Unlike conventional static race detectors, ECHO warns developers of potential data races immediately as they are introduced into the program. The core underpinning ECHO is a set of new change-aware static analyses based on a novel static happens-before graph that, given a program change, efficiently compute the change-relevant information without re-analyzing the whole program. Our evaluation within a Java environment on both popular benchmarks and real- world applications shows promising results: for each code addition, or deletion, ECHO can instantly pinpoint all the races in a few milliseconds on average, three to four orders of magnitude faster than a conventional whole-program race detector with the same precision. Sheng Zhan, Jeff Huang 0001 |
SIGSOFT FSE | 1 |