MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna and ML-Quadrat

Jörg Christian Kirchhof, Evgeny Kusmenko, Jonas Ritz, Bernhard Rumpe, Armin Moin, Atta Badii, Stephan Günnemann, Moharram Challenger

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

5 Zitate (Scopus)

Abstract

In this paper, we propose to adopt the MDE paradigm for the development of Machine Learning (ML)-enabled software systems with a focus on the Internet of Things (IoT) domain. We illustrate how two state-of-The-Art open-source modeling tools, namely MontiAnna and ML-Quadrat can be used for this purpose as demonstrated through a case study. The case study illustrates using ML, in particular deep Artificial Neural Networks (ANNs), for automated image recognition of handwritten digits using the MNIST reference dataset, and integrating the machine learning components into an IoT-system. Subsequently, we conduct a functional comparison of the two frameworks, setting out an analysis base to include a broad range of design considerations, such as the problem domain, methods for the ML integration into larger systems, and supported ML methods, as well as topics of recent intense interest to the ML community, such as AutoML and MLOps. Accordingly, this paper is focused on elucidating the potential of the MDE approach in the ML domain. This supports the ML-engineer in developing the (ML/software) model rather than implementing the code, and additionally enforces reusability and modularity of the design through enabling the out-of-The-box integration of ML functionality as a component of the IoT or cyber-physical systems.

OriginalspracheEnglisch
TitelProceedings - ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems, MODELS 2022
UntertitelCompanion Proceedings
Herausgeber (Verlag)Association for Computing Machinery, Inc
Seiten380-387
Seitenumfang8
ISBN (elektronisch)9781450394673
DOIs
PublikationsstatusVeröffentlicht - 23 Okt. 2022
Veranstaltung25th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2022 - Montreal, Kanada
Dauer: 23 Okt. 202228 Okt. 2022

Publikationsreihe

NameProceedings - ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems, MODELS 2022: Companion Proceedings

Konferenz

Konferenz25th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2022
Land/GebietKanada
OrtMontreal
Zeitraum23/10/2228/10/22

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