Skip to content

sraedler/MDE_for_ML_Generation

Repository files navigation

Model-Driven Engineering (MDE) approach to generate Machine Learning Code based on SysML and Mapping Configuration

General information

This repository contains code for the Proof-of-concept (PoC) implementation done for a Master of Science in Information and Software Engineering at the University of Applied Sciences Dornbirn.

This work was supervised and conceptually elaborated at the Chair of Information Systems and Business Process Management (i17), Department of Computer Science, Technical University of Munich

Description

This PoC implementation is based on a recently published approach to machine learning modeling with SysML at INDIN 2022 (Radler, S., Rigger, E., Mangler, J., Rinderle-Ma, S., 2022. Integration of Machine Learning Task Definition in Model-Based Systems Engineering using SysML, in: 2022 IEEE 20th International Conference on Industrial Informatics (INDIN). Presented at the 2022 IEEE 20th International Conference on Industrial Informatics (INDIN), IEEE, Perth, Australia, pp. 546–551. https://doi.org/10.1109/INDIN51773.2022.9976107).

The goals of the PoC implementation are as follows:

  • Use of an existing SysML profile for machine learning (ML) modeling, which can be used to describe data, interfaces, ML processing, and to define ML algorithms
  • Develop a model transformation to extract information from the SysML model into the intermediate model. The intermediate model must be defined as a metamodel beforehand
  • Generating executable ML code from a SysML model using the intermediate model and template-based code generation
  • Definition of ML templates for specific stereotypes from the user-defined SysML profile, which are used as the basis for generation
  • Provide a mapping configuration mechanism that allows the user to map SysML elements to template variables and exchange them dynamically

Structure

Folder Content
csv Input csv files for the case study.
images Screenshots of the SysML model with stereotypes.
mappings The mapping configuration used to map stereotypes with template files in "templates"
savedNotebook The result of the applied model transformation (can be regenerated by running the code)
src The source code for the model transformation
SysMLModels A sample SysML model that is used for the specified use case
templates The templates used during the generation for the specific stereotypes

Contact Us

About

Model-Driven Engineering approach to generate Machine Learning code based on SysML formalization

Topics

Resources

License

Stars

Watchers

Forks

Contributors 2

  •  
  •