Logo des Repositoriums

Auflistung nach Schlagwort "Model-Driven Engineering"

1 - 7 von 7
  • Konferenzbeitrag
    From Natural Language to Web Applications: Using Large Language Models for Model-Driven Software Engineering
    (Modellierung 2024, 2024) Netz, Lukas; Michael, Judith; Rumpe, Bernhard
    We evaluate the usage of Large Language Models (LLMs) to transform natural language into models of a predefined domain-specific language within the context of model-driven software engineering. In this work we test systematically the reliability and correctness of the developed tooling, to ensure its usability in an automated model-driven engineering context. Up to now, LLMs such as ChatGPT were not sophisticated enough to yield promising results. The new API-Access and the release of GPT-4, enabled us to develop improved tooling that can be evaluated systematically. This paper introduces an approach that can produce a running web application based on simple informal specifications, that is provided by a domain expert with no prior knowledge of any DSL. We extended our toolchain to include ChatGPT and provided the AI with additional DSL-specific contexts in order to receive models that can be further processed. We performed tests to ensure the semantic and syntactic correctness of the created models. This approach shows the potential of LLMs to successfully bridge the gap between domain experts and developers and discusses its current limitations.
  • Konferenzbeitrag
    A Graph-Based Framework for Model-Driven Optimization Facilitating Impact Analysis of Mutation Operator Properties
    (Software Engineering 2024 (SE 2024), 2024) John, Stefan; Kosiol, Jens; Lambers, Leen; Taentzer, Gabriele
  • Konferenzbeitrag
    Maintaining Consistency across Engineering Artifacts
    (Software Engineering 2020, 2020) Egyed, Alexander; Zeman, Klaus; Hehenberger, Peter; Demuth, Andreas; Zimmermann, Larissa Cardoso; Kretschmer, Roland
    Abstract: We summarize the paper Maintaining Consistency across Engineering Artifacts, published at IEEE Computer 51(2), pp. 28-35, 2018. Detecting inconsistencies across multi-domain and multi-tool artifacts is an important and critical task. Inconsistencies may lead to project failures, cost, and schedule overrun - especially when identified incorrectly or late. The paper we summarize explores a technology for consistency checking that is able to automatically and continuously detect inconsistencies - both among knowledge within and across engineering tools.
  • Konferenzbeitrag
    Model-Driven Engineering for Machine Learning Code Generation using SysML
    (Modellierung 2024, 2024) Rädler, Simon; Rupp, Matthias; Rigger, Eugen; Rinderle-Ma, Stefanie
    The complexity of engineering products increases due to more functions, components, and the number of involved disciplines. In this respect, Data-Driven Engineering (DDE) aims to integrate machine learning to support product development and help manage the increasing complexity of engineered systems. Still, the potential and opportunities of DDE are not entirely reflected in practice, which among others originate from the rarely available machine learning experts on the market and the effort for the implementation in practice. In this respect, this work depicts an approach based on model-driven engineering, allowing to automatically derive executable machine learning code based on machine learning task formalization using the general-purpose modeling language SysML. The main focus of the approach is on the generality of the model transformation using templates so that extensions and changes to the code generation can be integrated without requiring profound modifications to the code generator. The approach is evaluated in a use case in the domain of Cyber-Physical Systems, i.e., weather forecast prediction based on data from a Cyber-Physical weather system. The derived executable code promises to reduce the time for the implementation and supports the standardization of machine learning implementations within a company due to templates.
  • Konferenzbeitrag
    Reasoning about Product-Line Evolution using Complex Feature Model Differences
    (Software Engineering 2017, 2017) Bürdek, Johannes; Kehrer, Timo; Lochau, Malte; Reuling, Dennis; Kelter, Udo; Schürr, Andy
    In this work, we report about research results on the Reasoning about Product-Line Evo- lution using Complex Feature Model Differences, published in [Bu ̈15]. A (software) product-line constitutes a long-term investment and, therefore, has to undergo continuous evolution to meet con- stantly changing requirements. Initially, product-line evolution leads to changes of the variability model, typically a feature model, due to its central role in the product-line paradigm. Thus, product- line engineers are often faced with the problems that (1) feature models are changed ad-hoc without proper documentation, and (2) the semantic impact of changes is unclear. We propose a comprehen- sive approach to tackle both challenges. For (1), our approach compares the old and new version of the diagram representation of a feature model and specifies the changes using edit operations on feature diagrams. For (2), we propose a novel approach for reasoning about the semantic impact of diagram changes. We present a set of edit operations on feature diagrams, where complex operations are primarily derived from evolution scenarios observed in a real-world case study. We demonstrate the applicability of our approach with respect to the case study, and evaluate its scalability concern- ing experimental data sets.
  • Konferenzbeitrag
    Softwareentwicklung wie am Fließband
    (Software Engineering 2020, 2020) Koch, Thorsten; Meyer, Matthias; Fazal-Baqaie, Masud; Runschke, Hubert
    Unternehmen des Maschinen- und Anlagenbaus sind bestrebt, Entwicklungs- und Inbetriebnahme-zeiten für Anlagen zu reduzieren und damit den Absatz zu erhöhen. Der Steuerungscode dieser Anlagen wird typischerweise nicht auf Basis anerkannter Softwaretechnik-Methoden entwickelt und nur unsystematisch per Copy & Paste wiederverwendet. Die Anwendung von moderner Software-technik und insbesondere die modellgetriebene Entwicklung bergen daher ein großes Potential für die Steigerung der Qualität und Effizienz. Allerdings meiden Unternehmen die damit verbundene Komplexität und Investitionskosten. Wir präsentieren ein Stufen-Modell für die Verbesserung der Softwareentwicklung, das leichter von Unternehmen adaptierbar ist und berichten von unseren Erfahrungen mit dem Industriepartner Venjakob bei dessen Anwendung.
  • Konferenzbeitrag
    A Survey of Analysis Composition Operators in the Context of Palladio
    (Softwaretechnik-Trends Band 43, Heft 4, 2023) Taghavi, Bahareh; Weber, Sebastian
    Model-Based Analysis is an approach in Model-Driven Engineering that uses models to systematically analyze a system for structure, behavior, or quality characteristics. Due to the complexity and interdependence of modern systems, individual analysis approaches need to be combined to meet a specific purpose and achieve complete analysis. This paper provides an overview of current analysis composition operators in the context of Palladio, along with examples of how they are used. The objective is to define some criteria that aid in the judicious selection of the most fitting operator for distinct scenarios.