Demo Data from EDBT 2026 / reviewers in the wild / expert
Marco Radavelli
dblp:186/1055
· DBLP profile ↗
6ranked-venue papers
2as first author
0since 2021 · last 2019
0000-0002-1165-9981ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 5 · 2 first-authorArtificial intelligence and machine learning · 2Graphics, computer vision, multimedia, augmented reality and games · 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 |
Requirements engineering and software design · 77% Software testing · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design › inconsistency management
model repair |
0.4 | 1 | 2019 | Using software testing to repair models · ESEC/SIGSOFT FSE 2019 |
Methods — techniques the papers use, named apart from their topics
software testing · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Using Testing to Repair ModelsabstractSoftware testing is an important phase in the software development process, aiming at locating faults in artifacts, in order to achieve a degree of confidence that the software behaves according to a specification. While most of the techniques in software testing are applied to debugging, fault-localization, and repair of code, to the best of our knowledge there are fewer works regarding the application of software testing to locating faults in models and to the automated repair of such faults. The goal of this PhD project proposal is to study how testing can be applied to repair models. We describe the research approach and discuss the application cases of combinatorial and feature models. We then discuss future work of applying testing to repair models for other scenarios, such as timed automata. Marco Radavelli |
ICST | 1 |
| 2019 | A Fault-Driven Combinatorial Process for Model Evolution in XSS Vulnerability Detection
Bernhard Garn, Marco Radavelli, Angelo Gargantini, Manuel Leithner, Dimitris E. Simos |
IEA/AIE | 2 |
| 2019 | Combining Model Refinement and Test Generation for Conformance Testing of the IEEE PHD Protocol Using Abstract State Machines
Andrea Bombarda, Silvia Bonfanti, Angelo Gargantini, Marco Radavelli, Feng Duan 0002, Yu Lei 0001 |
ICTSS | 4 |
| 2019 | Using software testing to repair models
Marco Radavelli |
ESEC/SIGSOFT FSE | 1 |
| 2019 | Achieving change requirements of feature models by an evolutionary approach
Paolo Arcaini, Angelo Gargantini, Marco Radavelli |
J. Syst. Softw. | 3 |
| 2016 | Validation of Constraints Among Configuration Parameters Using Search-Based Combinatorial Interaction Testing
Angelo Gargantini, Justyna Petke, Marco Radavelli, Paolo Vavassori |
SSBSE | 3 |