Auflistung nach Autor:in "Kugele, Stefan"
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- Konferenzbeitrag20th Workshop on Automotive Software Engineering (ASE'23)(Software Engineering 2023 Workshops, 2023) Kugele, Stefan; Grunske, LarsSoftware-based systems play an increasingly important role and enable most innovations in modern cars. This workshop will address various topics related to automotive software development. The participants will discuss appropriate methods, techniques, and tools needed to address the most current challenges for researchers and practitioners.
- Konferenzbeitrag20th Workshop on Automotive Software Engineering (ASE’23)(Software Engineering 2023, 2023) Kugele, Stefan; Grunske, LarsSoftware-based systems play an increasingly important role and enable most innovations in modern cars. This workshop will address various topics related to automotive software development. The participants will discuss appropriate methods, techniques, and tools needed to address the most current challenges for researchers and practitioners.
- Konferenzbeitrag21st Workshop on Automotive Software Engineering (ASE'24)(Software Engineering 2024 (SE 2024), 2024) Kugele, Stefan; Wotawa, Franz
- KonferenzbeitragModel-based resource analysis and synthesis of service-oriented automotive software architectures(Software Engineering 2022, 2022) Kugele, Stefan; Obergfell, Philipp; Sax, EricThis summary refers to the paper ''Model-based resource analysis and synthesis of service-oriented automotive software architectures.'' This paper has been published in the Journal on Software and Systems Modeling (SoSyM) in September 2021. Context: One drawback of today's automotive software architectures is their strong integration into the onboard communication network based on predefined dependencies at design time. The idea is to reduce this rigid integration and technological dependencies by using a service-oriented architecture (SOA) that dynamically regulates network communication at run-time. Aim: We target to provide a methodology for analysing hardware resources and synthesising automotive service-oriented architectures based on platform-independent service models that are transformed in a subsequent step into a platform-specific architecture realisation process. Approach: For the first part, we apply design space exploration and simulation to derive analysed deployment configurations at an early development stage. We refine these configurations to AUTOSAR Adaptive software architecture models required for a subsequent implementation process for the platform-specific part. Result: We present optimal deployment configurations for our next generation of E/E architecture. We also provide simulation results that demonstrate the ability of these configurations to meet the run time requirements.
- TextdokumentResearch Challenges for a Future-Proof E/E Architecture - A Project Statement(INFORMATIK 2017, 2017) Kugele, Stefan; Cebotari, Vadim; Gleirscher, Mario; Hashemi, Morteza; Segler, Christoph; Shafaei, Sina; Vögel, Hans-Jörg; Bauer, Fridolin; Knoll, Alois; Marmsoler, Diego; Michel, Hans-UlrichDuring the last decades, the functional power and complexity of automotive E/E architectures grew radically and is going to grow further. We identified two key factors namely autonomy and intelligence. Both pose research challenges for the next generation E/E architecture. We aim to tackle the design challenges with methods and technologies. We propose in this project statement to use a service-oriented architecture on top of an in-vehicle communication network based on time-sensitive networking. Moreover, a rigor risk analysis and mitigation approach enables synthesis of a safety controller. A learning architecture facilitates a shift towards user centralization by proactively adapting functions according to user profiles. In addition, further functions might need to be learned at run-time.