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Vorträge
Automatic Component Diagram Generation from Natural Language Specifications
| Vortragende(r)
|
Marco Demartino
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| Vortragstyp
|
Bachelorarbeit
|
| Betreuer(in)
|
Vincenzo Scotti
|
| Vortragssprache
|
Englisch
|
| Vortragsmodus
|
in Präsenz
|
| Kurzfassung
|
This thesis investigates the automatic generation of UML component diagrams from natural language descriptions using large language models (LLMs). UML diagrams are widely used in software architecture documentation, but creating them manually can be time-consuming and requires expertise in modeling languages. The proposed approach introduces a generation pipeline that transforms textual specifications into structured component models, using prompt engineering techniques such as few-shot learning to guide the model toward syntactically valid and semantically meaningful outputs. An evaluation framework is defined to assess the generated diagrams with respect to both syntactic correctness and semantic alignment with the input descriptions. Initial experimental results are promising, suggesting that LLMs can effectively support the generation of UML component diagrams. In the future, LLMs could be integrated into automated pipelines to generate architecture diagrams more quickly and reduce the manual effort required in software documentation.
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Generating Digital Twin Code Components from Formal Interface Models in the Automotive Domain
| Vortragende(r)
|
Robin Schöppner
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| Vortragstyp
|
Masterarbeit
|
| Betreuer(in)
|
Erik Burger
|
| Vortragssprache
|
Deutsch
|
| Vortragsmodus
|
in Präsenz
|
| Kurzfassung
|
The automotive industry is in the midst of a shift from traditionally distributed systems of independent control units towards a more centralized E/E architecture. A prominent challenge in this transition is the integration of heterogeneous software components from diverse suppliers. Traditionally, this gap is bridged by manually written integration code, leading to tight coupling between domain logic and communication protocols, which makes system evolution difficult.
This thesis presents a model-driven approach for generating digital twin code components directly from formal descriptions of in-vehicle components. Central to the approach is the generation of a stable core domain model that represents the vehicle state. Connections to physical hardware are abstracted via a generic interface and the COVESA Interface Exchange Framework (IFEX) as a standardized contract layer. By implementing the communication patterns once generically, the approach eliminates the need for manual integration code for individual components or new requirements.
This centralized state representation further enables a simplified off-board cloud twin instance to be fully synchronized with the on-board twin. This architecture generically supports remote control and monitoring of any vehicle function, regardless of whether that functionality was originally designed for online connectivity. The approach is validated by implementing a prototypical code generation pipeline, deploying it on distributed virtual machines, and connecting mock ECUs using different Interface Definition Languages (gRPC, SOME/IP). The evaluation demonstrates that changing underlying communication protocols requires only a model update without modifying domain code.
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Preventing Advanced Dead Code Attacks on Source Code Plagiarism Detection via Abstract Interpretation
| Vortragende(r)
|
Leon Bruns
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| Vortragstyp
|
Bachelorarbeit
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| Betreuer(in)
|
Robin Maisch
|
| Vortragssprache
|
Deutsch
|
| Vortragsmodus
|
in Präsenz
|
| Kurzfassung
|
Code plagiarism in academic contexts, most notably in first-year programming courses, continues to be a problem. Currently, the most widely used plagiarism detectors are vulnerable to plagiarism obfuscation through inserted complex dead code. We propose using abstract interpretation to detect and remove dead code before the code is processed by plagiarism detection tools.
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