activity
20212024
most citedQuantifying and combining uncertainty for improving the behavior of Digital Twin Systems

2 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE20241 cited

Human Factors in Model-Driven Engineering: Future Research Goals and Initiatives for MDE

Grischa Liebel, Jil Klünder, Regina Hebig +23

Purpose: Software modelling and Model-Driven Engineering (MDE) is traditionally studied from a technical perspective. However, one of the core motivations behind the use of softwar…

cs.SE2024

An Extensible Framework for Architecture-Based Data Flow Analysis for Information Security

Nicolas Boltz, Sebastian Hahner, Christopher Gerking +1

The growing interconnection between software systems increases the need for security already at design time. Security-related properties like confidentiality are often analyzed bas…

eess.SY20242 cited

Quantifying and combining uncertainty for improving the behavior of Digital Twin Systems

Julien Deantoni, Paula Muñoz, Cláudio Gomes +5

Uncertainty is an inherent property of any complex system, especially those that integrate physical parts or operate in real environments. In this paper, we focus on the Digital Tw…

cs.SE2024

Quantifying Software Correctness by Combining Architecture Modeling and Formal Program Analysis

Florian Lanzinger, Christian Martin, Frederik Reiche +3

Most formal methods see the correctness of a software system as a binary decision. However, proving the correctness of complex systems completely is difficult because they are comp…

cs.SE20231 cited

Tool-Supported Architecture-Based Data Flow Analysis for Confidentiality

Felix Schwickerath, Nicolas Boltz, Sebastian Hahner +3

Through the increasing interconnection between various systems, the need for confidential systems is increasing. Confidential systems share data only with authorized entities. Howe…

cs.AI2021

Towards fuzzification of adaptation rules in self-adaptive architectures

Tomáš Bureš, Petr Hnětynka, Martin Kruliš +5

In this paper, we focus on exploiting neural networks for the analysis and planning stage in self-adaptive architectures. The studied motivating cases in the paper involve existing…