Markus Schweizer

dblp:195/3809 · DBLP profile ↗
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7ranked-venue papers
0as first author
3since 2021 · last 2025
0000-0001-6881-8499ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 3 · 3 since 2021Security and privacy · 2Systems, architecture and hardware · 1Graphics, computer vision, multimedia, augmented reality and games · 1
YearPublicationVenuePosition
2025 Runtime Monitor Synthesis for Automotive Software Architectures
Fazli Faruk Okumus, João-Vitor Zacchi, Maike Salfeld, Markus Schweizer, Núria Mata, Stefan Kugele
ECSA4
2025 Regulatory Compliance-Aware System Change Management via an Ontology-Based Approach
Barbara Gallina, Markus Schweizer, Henrik Dibowski
EuroSPI (1)2
2024 An Ontology-Based Representation for Shaping Product Evolution in Regulated Industries
Barbara Gallina, Henrik Dibowski, Markus Schweizer
ICSR3
2020 Model-Based Safety Analysis of Mode Transitions
Marco Bozzano, Peter Munk, Markus Schweizer, Stefano Tonetta, Viktória Vozárová
SAFECOMP3
2018 Semi-automatic safety analysis and optimization
abstract
The complexity of safety-critical E/E-systems within the automotive domain are continuously increasing. At the same time, functional safety standards such as the ISO 26262 prescribe analysis methods like the Fault Tree Analysis (FTA) and Failure Mode and Effects Analysis (FMEA). Currently, these analysis methods are mainly performed manually and are often not consistent with an evolving system model.
Peter Munk, Andreas Abele, Eike Thaden, Arne Nordmann, Rakshith Amarnath, Markus Schweizer, Simon Burton 0001
DAC6
2018 A Model-Based Safety Analysis of Dependencies Across Abstraction Layers
Christoph Dropmann, Eike Thaden, Mario Trapp, Denis Uecker, Rakshith Amarnath, Leandro Avila da Silva, Peter Munk, Markus Schweizer, Matthias Jung 0001, Rasmus Adler
SAFECOMP8
2017 Visual Comparison of Eye Movement Patterns
abstract
Abstract In eye tracking research, finding eye movement patterns and similar strategies between participants’ eye movements is important to understand task solving strategies and obstacles. In this application paper, we present a graph comparison method using radial graphs that show Areas of Interest (AOIs) and their transitions. An analyst investigates a single graph based on dwell times, directed transitions, and temporal AOI sequences. Two graphs can be compared directly and temporal changes may be analyzed. A list and matrix approach facilitate the analyst to contrast more than two graphs guided by visually encoded graph similarities. We evaluated our approach in case studies with three eye tracking and visualization experts. They identified temporal transition patterns of eye movements across participants, groups of participants, and outliers.
Tanja Blascheck, Markus Schweizer, Fabian Beck 0001, Thomas Ertl
Comput. Graph. Forum2