Demo Data from VLDB 2026 / reviewers in the wild / expert
Lee Chew
dblp:57/8290
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author
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 |
Concurrent programming · 67% Program analysis · 33% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Processor architecture and microarchitecture · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Concurrent programming › concurrency bugs
atomicity violation |
0.1 | 1 | 2010 | Kivati: fast detection and prevention of atomicity violations · EuroSys 2010 |
Concurrent programming
concurrency bugs |
0.1 | 1 | 2010 | Kivati: fast detection and prevention of atomicity violations · EuroSys 2010 |
Program analysis
dynamic analysis |
0.1 | 1 | 2010 | Kivati: fast detection and prevention of atomicity violations · EuroSys 2010 |
Methods — techniques the papers use, named apart from their topics
static analysis · 0.2dynamic reordering · 0.2hardware watchpoints · 0.1hardware watchpoint · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Kivati: fast detection and prevention of atomicity violationsabstractBugs in concurrent programs are extremely difficult to find and fix during testing. In this paper, we propose Kivati, which can efficiently detect and prevent atomicity violation bugs. Kivati imposes an average run-time overhead of 19%, which makes it practical to deploy on software in production environments. The key attribute that allows Kivati to impose this low overhead is its use of hardware watchpoints, which can be found on most commodity processors. Kivati combines watchpoints with a simple static analysis that annotates regions of codes that likely need to be executed atomically. The watchpoints are then used to monitor these regions for interleaving accesses that may lead to an atomicity violation. When an atomicity violation is detected, Kivati dynamically reorders the access to prevent the violation from occurring. Kivati can be run in prevention mode, which optimizes for performance, or in bug-finding mode, which trades some performance for an enhanced ability to find bugs. Lee Chew, David Lie |
EuroSys | 1 |