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F. Rinker, L. Waltersdorfer, S. Biffl:
"Towards Test-Driven Model Development in Production Systems Engineering";
Talk: Online Conference 22nd International Conference on Enterprise Information Systems (ICEIS 2020), Online; 2020-05-05 - 2020-05-07; in: "Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS", ScitePress, (2020), ISBN: 978-989-758-423-7; 213 - 219.

The correct representation of discipline-specific and cross-specific knowledge in manufacturing contexts is
becoming more important due to inter-disciplinary dependencies and overall higher system complexity. However, domain experts do seldom have sufficient technical and theoretical knowledge or adequate tool support
required for productive and effective model engineering and validation. Furthermore, increasing competition and faster product lifecycle require the need for parallel collaborative engineering efforts from different
workgroups. Thus, test-driven modeling, similar to test-driven software engineering can support the model
engineering process to produce high-quality meta and instance models by incorporating consistency and semantic checks during the model engineering. We present a conceptual framework for model transformation
with testing and debugging capabilities for production system engineering use cases supporting the modeling of discipline-specific AutomationML instance models. An exemplary workflow is presented and discussed. Debug output for the models is generated to support non-technical engineers in the error detection of
discipline-specific models. For future work user-friendly test definition is in planning.

Test-Driven Model Engineering, Production Systems Engineering, Meta-Model Engineering, Testing Pipeline, Test-Driven Model Development, experience report

http://dx.doi.org/10.5220/0009425302130219