Projects per year
Abstract
DevOps and Model Driven Engineering (MDE) provide differently skilled IT stakeholders with methodologies and tools for organizing and automating continuous software engineering activities-from development to operations, and using models as key engineering artifacts, respectively. Both DevOps and MDE aim at shortening the development life-cycle, dealing with complexity, and improve software process and product quality.
The integration of DevOps and MDE principles and practices in low-code engineering platforms (LCEP) are gaining attention by the research community. However, at the same time, new requirements are upcoming for DevOps and MDE as LCEPs are often used by non-technical users, to deliver fully functional software. This is in particular challenging for current DevOps processes, which are mostly considered on the technological level, and thus, excluding most of the current LCEP users. The systematic use of models and modeling to lowering the learning curve of DevOps processes and platforms seems beneficial to make them also accessible for non-technical users.
In this paper, we introduce DevOpsML, a conceptual framework for modeling and combining DevOps processes and platforms. Tools along with their interfaces and capabilities are the building blocks of DevOps platform configurations, which can be mapped to software engineering processes of arbitrary complexity. We show our initial endeavors on DevOpsML and present a research roadmap how to employ the resulting DevOpsML framework for different use cases.
Original language | English |
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Title of host publication | MODELS 2020, Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, October 16-23, 2020. |
Pages | 69:1-69:10 |
Number of pages | 10 |
DOIs | |
Publication status | Published - Oct 2020 |
Fields of science
- 202017 Embedded systems
- 102002 Augmented reality
- 102006 Computer supported cooperative work (CSCW)
- 102015 Information systems
- 102020 Medical informatics
- 102022 Software development
- 102034 Cyber-physical systems
- 201132 Computational engineering
- 201305 Traffic engineering
- 207409 Navigation systems
- 502032 Quality management
- 502050 Business informatics
- 503015 Subject didactics of technical sciences
JKU Focus areas
- Digital Transformation
Projects
- 1 Finished
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CDL-MINT Christian Doppler Laboratory for Model-Integrated Smart Production
Eisenberg, M. (Researcher), Gemeinhardt, F. (Researcher), Govindasami, H. S. (Researcher), Jayaraman, R. (Researcher), Mitter, A. (Researcher), Sindelar, R. (Researcher), Sint, S. (Researcher), Taspinar, B. (Researcher) & Wimmer, M. (PI)
01.01.2017 → 31.12.2023
Project: Funded research › Other sponsors