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Sheng Zhan

dblp:190/1159 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Concurrent programming › concurrency bug detection
data race detection
0.212016
ECHO: instantaneous in situ race detection in the IDE · SIGSOFT FSE 2016
Program analysis › concurrent program analysis
static race detection
0.212016
ECHO: instantaneous in situ race detection in the IDE · SIGSOFT FSE 2016
Program analysis
static analysis
0.112016
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
YearPublicationVenuePosition
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 IDE
abstract
We 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 FSE1