EDBT 2026 Demo / reviewers in the wild / expert
Monika Muzikovská
dblp:223/0264
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1
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 · 44% Concurrent programming · 44% Software testing · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Concurrent programming
concurrency analysis |
0.3 | 1 | 2018 | Advances in the ANaConDA framework for dynamic analysis and testing of concurrent C/C++ programs · ISSTA 2018 |
Program analysis
dynamic analysis |
0.3 | 1 | 2018 | Advances in the ANaConDA framework for dynamic analysis and testing of concurrent C/C++ programs · ISSTA 2018 |
Software testing
concurrency testing |
0.1 | 1 | 2018 | Advances in the ANaConDA framework for dynamic analysis and testing of concurrent C/C++ programs · ISSTA 2018 |
Methods — techniques the papers use, named apart from their topics
noise injection · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Advances in the ANaConDA framework for dynamic analysis and testing of concurrent C/C++ programsabstractThe paper presents advances in the ANaConDA framework for dynamic analysis and testing of concurrent C/C++ programs. ANaConDA comes with several built-in analysers, covering detection of data races, deadlocks, or contract violations, and allows for an easy creation of new analysers. To increase the variety of tested interleavings, ANaConDA offers various noise injection techniques. The framework performs the analysis on a binary level, thus not requiring the source code of the program to be available. Apart from many academic experiments, ANaConDA has also been successfully used to discover various errors in industrial code. Jan Fiedor, Monika Muzikovská, Ales Smrcka, Ondrej Vasícek, Tomás Vojnar |
ISSTA | 2 |