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
- TextdokumentCause-Effect Chain-Based Diagnosis of Automotive On-Board Energy Systems(Software Engineering 2025, 2025) Kugele, Stefan; Schreyer, Lorenz; Lamprecht, MartinContext: Vehicle diagnostics are critical tools for identifying, locating, and resolving automobile faults. However, the increasing connectivity within vehicles poses challenges to seamless diagnostic processes. Aim: This paper aims to improve the rectification of faults following a diagnostic trouble code entry in a vehicle’s electrical power system. Method: The approach involves designing a graph based on the cause-effect chain from the ‘flexible Energy and Power Management’ (fEPM) detailed model, defining areas for each signal to identify potential causes for diagnostic trouble code entries using simulated signal traces. This method and graph reduction techniques were evaluated through an interview study with engineers who provided feedback on its practical applicability and efficacy in real-world scenarios. Results: The application of this method results in a clear fault image, graphically representing the origin of the diagnostic trouble code entry. This reduced graph can be interpreted comprehensively for each component and each diagnostic trouble code entry, possibly automating the interpretation process. The interview study confirmed the applicability and efficiency of the approach. Conclusion: This research presents a method for identifying the root causes of faults in automotive
- 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.
- TextdokumentWorkshop Summary(Software Engineering 2025 – Companion Proceedings, 2025) Henß, Jörg; Kugele, StefanSoftware-driven systems are becoming pivotal, underpinning the majority of innovations in contemporary automobiles. This workshop is poised to explore a plethora of topics pertinent to automotive software development. Attendees will engage in discourse on the most apt methodologies, techniques, and tools essential for navigating the foremost challenges faced by researchers and practitioners in the field.