Stammdaten

Titel: Model-Based Generation of Software Configurations in Mechatronic Systems
Untertitel:
Kurzfassung:

An essential part of the mechatronic system is the software, which is responsible to bring functionality into the system consisting of mechanical, electronic and electrical parts. The software must be tailored to the specific hardware to fulfill tasks (e.g. control, monitoring) according to the system requirements. In today‘s industrial practice, the design is mainly done manually. First the entire architecture is drawn using drawing tools. Based on this software developers derive the low-level specification using their low-level development environments. This is error prone and time-consuming due to the fact, that a large number of hardware parameters have to be taken in account and the informal specification does not allow to derive these parameters. To improve this we present here an approach where the overall architecture of the mechatronic system is described using a Domain-Specific Conceptual Modeling Language (DSML) using the example of Electric Vehicle Testbeds. Based on this model the low-level software configurations are generated rule-based. In this paper we present the concepts of the DSML, explain the transformation rules and show the functionality of the generator by introducing a practical example.

Schlagworte: Modeling; Metamodel; DSML; Software; Generator; Transformation; Configuration
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 05.05.2020 (Print)
Erschienen in: 40 Years EMISA - Digital Ecosystems of the Future: Methodology, Techniques and Applications. Proc. 40th Conf. of the GI SIG EMISA
40 Years EMISA - Digital Ecosystems of the Future: Methodology, Techniques and Applications. Proc. 40th Conf. of the GI SIG EMISA (2020)

H. Mayr, S. Rinderle-Ma, S. Strecker
Gesellschaft für Informatik e.V.

zur Publikation
 ( Gesellschaft für Informatik e.V.; H. Mayr, S. Rinderle-Ma, S. Strecker )
Titel der Serie: Lecture Notes in Informatics
Bandnummer: P-302
Erstveröffentlichung: Ja
Seite: S. 29 - 44

Versionen

Keine Version vorhanden
Erscheinungsdatum: 05.05.2020
ISBN:
  • 978-3-88579-698-5
ISSN: 1617-5468
Homepage: https://dl.gi.de/handle/20.500.12116/31845

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Österreich
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
zur Organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Kategorisierung

Sachgebiete
  • 102 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: n.a.)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Application Engineering

Kooperationen

Organisation Adresse
AVL List GmbH
Hans-List-Pl. 1
8010 Graz
Österreich - Steiermark
Hans-List-Pl. 1
AT - 8010  Graz

Beiträge der Publikation

Keine verknüpften Publikationen vorhanden