• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Model-Driven Approach for Automatic Model Information Aggregation in Structured Documents
 
  • Details
  • Full
Options
December 2023
Conference Paper
Title

Model-Driven Approach for Automatic Model Information Aggregation in Structured Documents

Abstract
While models are widely used in software development projects originating from industry and academic research, their documentation can be a time-intensive process. This paper focuses on providing a Proof of Concept for the automatic aggregation of various model data in two different document types conforming to ISO/IEC/IEEE 42010 architecture descriptions or instructional information documents according to ISO/IEC/IEEE 26514. Therefore, this work leverages a model-driven mapping approach of model information to the required document structure, dynamic templating algorithms to transform model data into text and a prototypical implementation that executes the defined mapping and transformation logic in practice. The generation results show that most of the documentation standard requirements can be fulfilled automatically and therefore, reduce the manual processing effort while enhancing consistency.
Author(s)
Henzgen, Arne
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Strey, Lukas  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Mainwork
ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023. Proceedings  
Conference
International Conference on Model Driven Engineering Languages and Systems Companion 2023  
DOI
10.1109/MODELS-C59198.2023.00072
Language
English
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Keyword(s)
  • Model-Driven Engineering

  • Documentation

  • BPMN

  • UML

  • GSN

  • Model-to-Documen

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024