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Lee Chew

dblp:57/8290 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Concurrent programming › concurrency bugs
atomicity violation
0.112010
Kivati: fast detection and prevention of atomicity violations · EuroSys 2010
Concurrent programming
concurrency bugs
0.112010
Kivati: fast detection and prevention of atomicity violations · EuroSys 2010
Program analysis
dynamic analysis
0.112010
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
YearPublicationVenuePosition
2010 Kivati: fast detection and prevention of atomicity violations
abstract
Bugs 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
EuroSys1