http://dl.gi.de/handle/20.500.12116/39455 2026-07-21T13:29:27Z http://dl.gi.de/handle/20.500.12116/14962 Optimal Product Line Architectures for the Automotive Industry Wägemann, Tobias; Tavakoli Kolagari, Ramin; Schmid, Klaus Schaefer, Ina; Karagiannis, Dimitris; Vogelsang, Andreas; Méndez, Daniel; Seidl, Christoph The creation of product line architectures is a difficult and complex task. The resulting architectures must support the required system variabilities as well as further quality attributes. In the automotive domain, product lines of software-intensive system models have a great diversity of products, which leads to vast design spaces. Finding optimal product line architectures as part of the system design process requires the consideration of a variety of trade-offs. In practice, this challenge cannot be solved manually for all but the smallest problems, therefore an automated solution is required. Our contribution is the generation of a sound mathematical formalization of the problem. This formalization makes the product line optimization problem accessible to various established multi-objective optimization techniques. The applicability of the chosen approach is shown by means of applying a commercial tool for multi-criteria decision making. 2018-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/14961 Exploiting Modular Language Extensions in Legacy C Code: An Automotive Case Study Grosche, Andreas; Igel, Burkhard; Spinczyk, Olaf Schaefer, Ina; Karagiannis, Dimitris; Vogelsang, Andreas; Méndez, Daniel; Seidl, Christoph Model-driven software development using language workbenches like JetBrains MPS provide many advantages compared to traditional software development. Base languages can be incrementally extended to increase the abstractness up to domain-specific languages (DSLs). Changes can be performed more efficiently in problem-oriented language extensions or DSLs, than in a base language. In addition, formal analysis can be performed on abstract models. To benefit from the model-driven approach, non-model-based legacy code has to be reusable and transformable to language extensions and DSLs. For the development of embedded systems, mbeddr provides a C99-like base language and extensions for MPS, such as mathematical symbols and state machines. This paper presents a case study that shows how many legacy C code fragments of three automotive series projects could be replaced by mbeddr language extensions. Furthermore, a proof of concept shows the feasibility of fraction and foreach loop refactorings. This work is a first approach for future language extension refactorings. 2018-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/14959 Towards a run-time model for data protection in the cloud Mann, Zoltan; Metzger, Andreas; Schoenen, Stefan Schaefer, Ina; Karagiannis, Dimitris; Vogelsang, Andreas; Méndez, Daniel; Seidl, Christoph The protection of sensitive data in the cloud is a challenge of increasing importance. It is made particularly difficult by the complex and dynamic interactions of many entities (hardware and software, as well as organizations and individuals). A model-based approach can be used to reason about these interactions and their impact on data protection during deployment and at run time. The basis for such an approach is a model of all relevant socio-technical cloud entities, which is created during deployment and kept alive at run-time to support adaptations. In this paper, we focus on the meta-model of this model. The meta-model is created during design and instantiated during deployment. We discuss what entities must be present in the meta-model to allow reasoning about data protection. In particular, we discuss to what extent the results of previous cloud modeling efforts can be reused and what extensions are necessary because of the particular requirements of data protection. 2018-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/14958 Transforming Enterprise Models to Linked Data via Semantic Annotations Pittl, Benedikt; Fill, Hans-Georg Schaefer, Ina; Karagiannis, Dimitris; Vogelsang, Andreas; Méndez, Daniel; Seidl, Christoph The use of conceptual models in enterprises is today a well-known fact. This includes many zdifferent types of models ranging from process models, organizational models, and infrastructure models to various types used in software engineering and technical systems development. Although these models are largely specified in a formal or at least semi-formal way, the knowledge contained in them is often only accessible via manual inspection. The primary reason for this shortcoming is the use of different formats for expressing models and the lack of machine-processable semantic specifications of the model content. In this paper we present a flexible approach for transforming information from such enterprise models to RDF. Thereby, we use a model weaving technique to annotate conceptual models with concepts from ontologies. For assessing its technical feasibility, the approach has been implemented on the SeMFIS platform and applied to a use case in the area of business process management. 2018-01-01T00:00:00Z