Demo Data from EDBT 2026 / reviewers in the wild / expert
Halil Ibrahim Ceylan
dblp:360/7066
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
0009-0005-1762-0286ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
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 · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Embedded and real-time systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › mutation testing
mutant generation |
0.7 | 1 | 2023 | MUT4SLX: Fast Mutant Generation for Simulink · ASE 2023 |
Software testing
mutation testing |
0.7 | 1 | 2023 | MUT4SLX: Fast Mutant Generation for Simulink · ASE 2023 |
Embedded and real-time systems
model-based design |
0.2 | 1 | 2023 | MUT4SLX: Fast Mutant Generation for Simulink · ASE 2023 |
Methods — techniques the papers use, named apart from their topics
mutation operators · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | MUT4SLX: Fast Mutant Generation for SimulinkabstractSeveral experience reports illustrate that mutation testing is capable of supporting a “shift-left” testing strategy for software systems coded in textual programming languages like C++. For graphical modelling languages like Simulink, such experience reports are missing, primarily because of a lack of adequate tool support. In this paper, we present a proof-of-concept (named MUT4S LX) for automatic mutant generation and test execution of Simulink models. MUT14SLX features 15 mutation operators which are modelled after realistic faults (mined from an industrial bug database) and are fast to inject (because we only replace parameter values within blocks). An experimental evaluation on a sample project (a Helicopter Control System) demonstrates that MUT4SLX is capable of injecting 70 mutants in less than a second, resulting in a total analysis time of 8.14 hours. Halil Ibrahim Ceylan, Onur Kilinççeker, Mutlu Beyazit, Serge Demeyer |
ASE | 1 |