Demo Data from SIGIR 2026 / reviewers in the wild / expert
Charles Lucas
dblp:120/2104
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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 |
Software testing · 91% Program analysis · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › system testing
distributed system testing |
0.1 | 1 | 2012 | Detecting problematic message sequences and frequencies in distributed systems · OOPSLA 2012 |
Software testing › automated testing
test driver generation |
0.1 | 1 | 2012 | Detecting problematic message sequences and frequencies in distributed systems · OOPSLA 2012 |
Software testing
test generation |
0.1 | 1 | 2012 | Detecting problematic message sequences and frequencies in distributed systems · OOPSLA 2012 |
Program analysis › symbolic execution
dynamic symbolic execution |
0.0 | 1 | 2012 | Detecting problematic message sequences and frequencies in distributed systems · OOPSLA 2012 |
Methods — techniques the papers use, named apart from their topics
dynamic symbolic execution · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Detecting problematic message sequences and frequencies in distributed systemsabstractTesting the components of a distributed system is challenging as it requires consideration of not just the state of a component, but also the sequence of messages it may receive from the rest of the system or the environment. Such messages may vary in type and content, and more particularly, in the frequency at which they are generated. All of these factors, in the right combination, may lead to faulty behavior. In this paper we present an approach to address these challenges by systematically analyzing a component in a distributed system to identify specific message sequences and frequencies at which a failure can occur. At the core of the analysis is the generation of a test driver that defines the space of message sequences to be generated, the exploration of that space through the use of dynamic symbolic execution, and the timing and analysis of the generated tests to identify problematic frequencies. We implemented our approach in the context of the popular Robotic Operating System and investigated its application to three systems of increasing complexity. Charles Lucas, Sebastian G. Elbaum, David S. Rosenblum |
OOPSLA | 1 |