Model-Driven Software Engineering to Foster the Adoption of Digital Twins
Resumo
Digital twins are virtual replicas of physical systems that offer significant benefits in terms of productivity and sustainability. However, most digital twin solutions are tailored to specific use cases, and there is a lack of domain-independent development frameworks. As a result, developers must build each system from scratch, which increases project timelines and costs and hinders the scalability of solutions. This ongoing doctoral project proposes a Model-Driven Software Engineering (MDSE) approach to simplify the development of digital twins. Ultimately, the presented approach aims to promote the widespread adoption of digital twins across sectors, making their development more accessible, scalable, and cost-effective.
Palavras-chave:
Digital Twins, Model-Driven Software Engineering, Domain-Specific Language, Model-to-Text Transformations
Referências
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Barriga, J. A., Chaves-González, J. M., Barriga, A., Alonso, P., and Clemente, P. J. (2023). Simulate iot towards the cloud-to-thing continuum paradigm for task scheduling assessments. J. Object Technol., 22(1):1–31.
Barriga, J. A., Clemente, P. J., Sosa-Sánchez, E., and Prieto, Á. E. (2021). Simulateiot: Domain specific language to design, code generation and execute iot simulation environments. IEEE Access, 9:92531–92552.
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Brambilla, M., Cabot, J., and Wimmer, M. (2017). Model-driven software engineering in practice. Morgan & Claypool Publishers.
Ciccozzi, F. and Spalazzese, R. (2016). Mde4iot: supporting the internet of things with model-driven engineering. In International Symposium on Intelligent and Distributed Computing, pages 67–76. Springer.
Dalibor, M., Michael, J., Rumpe, B., Varga, S., and Wortmann, A. (2020). Towards a model-driven architecture for interactive digital twin cockpits. In International Conference on Conceptual Modeling, pages 377–387. Springer.
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Fuller, A., Fan, Z., Day, C., and Barlow, C. (2020). Digital twin: Enabling technologies, challenges and open research. IEEE access, 8:108952–108971.
Hailpern, B. and Tarr, P. (2006). Model-driven development: The good, the bad, and the ugly. IBM systems journal, 45(3):451–461.
Hevner, A., Chatterjee, S., Hevner, A., and Chatterjee, S. (2010). Design science research in information systems. Design research in information systems: theory and practice, pages 9–22.
Ihirwe, F., Di Ruscio, D., Mazzini, S., Pierini, P., and Pierantonio, A. (2020). Low-code engineering for internet of things: a state of research. In Proceedings of the 23rd ACM/IEEE international conference on model driven engineering languages and systems: companion proceedings, pages 1–8.
Kolovos, D. S., García-Domínguez, A., Rose, L. M., and Paige, R. F. (2017). Eugenia: towards disciplined and automated development of gmf-based graphical model editors. Software & Systems Modeling, 16:229–255.
Lehner, D., Pfeiffer, J., Tinsel, E.-F., Strljic, M. M., Sint, S., Vierhauser, M., Wortmann, A., and Wimmer, M. (2021). Digital twin platforms: requirements, capabilities, and future prospects. IEEE Software, 39(2):53–61.
Macías, A., Navarro, E., Cuesta, C. E., and Zdun, U. (2023). Architecting digital twins using a domain-driven design-based approach. In 2023 IEEE 20th International Conference on Software Architecture (ICSA), pages 153–163. IEEE.
Mihai, S., Yaqoob, M., Hung, D. V., Davis, W., Towakel, P., Raza, M., Karamanoglu, M., Barn, B., Shetve, D., Prasad, R. V., et al. (2022). Digital twins: A survey on enabling technologies, challenges, trends and future prospects. IEEE Communications Surveys & Tutorials, 24(4):2255–2291.
Minerva, R., Lee, G. M., and Crespi, N. (2020). Digital twin in the iot context: A survey on technical features, scenarios, and architectural models. Proceedings of the IEEE, 108(10):1785–1824.
Moin, A., Rössler, S., and Günnemann, S. (2020). Thingml+ augmenting model-driven software engineering for the internet of things with machine learning. arXiv preprint arXiv:2009.10633.
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., and Bakiras, S. (2021). The role of ai, machine learning, and big data in digital twinning: A systematic literature review, challenges, and opportunities. IEEE Access, 9:32030–32052.
Segovia, M. and Garcia-Alfaro, J. (2022). Design, modeling and implementation of digital twins. Sensors, 22(14):5396.
Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., and Calinescu, A. (2022). Digital twins: State of the art theory and practice, challenges, and open research questions. Journal of Industrial Information Integration, 30:100383.
Stadtmann, F., Rasheed, A., Kvamsdal, T., Johannessen, K. A., San, O., Kölle, K., Tande, J. O., Barstad, I., Benhamou, A., Brathaug, T., et al. (2023). Digital twins in wind energy: Emerging technologies and industry-informed future directions. IEEE Access.
Stahl, T., Völter, M., and Czarnecki, K. (2006). Model-driven software development: technology, engineering, management. John Wiley & Sons, Inc.
Vale, S., Reddy, S., Subramanian, S., Chaudhuri, S. R., Nistala, S. H., Deodhar, A., and Runkana, V. (2023). A model-driven approach for knowledge-based engineering of industrial digital twins. In 2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS), pages 13–23. IEEE.
Wang, H., Chen, X., Jia, F., and Cheng, X. (2023). Digital twin-supported smart city: Status, challenges and future research directions. Expert Systems with Applications, 217:119531.
Barriga, J. A., Chaves-González, J. M., Barriga, A., Alonso, P., and Clemente, P. J. (2023). Simulate iot towards the cloud-to-thing continuum paradigm for task scheduling assessments. J. Object Technol., 22(1):1–31.
Barriga, J. A., Clemente, P. J., Sosa-Sánchez, E., and Prieto, Á. E. (2021). Simulateiot: Domain specific language to design, code generation and execute iot simulation environments. IEEE Access, 9:92531–92552.
Bibow, P., Dalibor, M., Hopmann, C., Mainz, B., Rumpe, B., Schmalzing, D., Schmitz, M., and Wortmann, A. (2020). Model-driven development of a digital twin for injection molding. In International Conference on Advanced Information Systems Engineering, pages 85–100. Springer.
Brambilla, M., Cabot, J., and Wimmer, M. (2017). Model-driven software engineering in practice. Morgan & Claypool Publishers.
Ciccozzi, F. and Spalazzese, R. (2016). Mde4iot: supporting the internet of things with model-driven engineering. In International Symposium on Intelligent and Distributed Computing, pages 67–76. Springer.
Dalibor, M., Michael, J., Rumpe, B., Varga, S., and Wortmann, A. (2020). Towards a model-driven architecture for interactive digital twin cockpits. In International Conference on Conceptual Modeling, pages 377–387. Springer.
Eclipse Foundation. Acceleo - generate anything from any emf model. [link]. Accessed: 2025-02-18.
Eclipse Foundation. Eclipse modeling tools. [link]. Accessed: 2025-02-18.
Eclipse Foundation. Sirius - the easiest way to get your own modeling tool. [link]. Accessed: 2025-02-18.
Friederich, J., Francis, D. P., Lazarova-Molnar, S., and Mohamed, N. (2022). A framework for data-driven digital twins of smart manufacturing systems. Computers in Industry, 136:103586.
Fuller, A., Fan, Z., Day, C., and Barlow, C. (2020). Digital twin: Enabling technologies, challenges and open research. IEEE access, 8:108952–108971.
Hailpern, B. and Tarr, P. (2006). Model-driven development: The good, the bad, and the ugly. IBM systems journal, 45(3):451–461.
Hevner, A., Chatterjee, S., Hevner, A., and Chatterjee, S. (2010). Design science research in information systems. Design research in information systems: theory and practice, pages 9–22.
Ihirwe, F., Di Ruscio, D., Mazzini, S., Pierini, P., and Pierantonio, A. (2020). Low-code engineering for internet of things: a state of research. In Proceedings of the 23rd ACM/IEEE international conference on model driven engineering languages and systems: companion proceedings, pages 1–8.
Kolovos, D. S., García-Domínguez, A., Rose, L. M., and Paige, R. F. (2017). Eugenia: towards disciplined and automated development of gmf-based graphical model editors. Software & Systems Modeling, 16:229–255.
Lehner, D., Pfeiffer, J., Tinsel, E.-F., Strljic, M. M., Sint, S., Vierhauser, M., Wortmann, A., and Wimmer, M. (2021). Digital twin platforms: requirements, capabilities, and future prospects. IEEE Software, 39(2):53–61.
Macías, A., Navarro, E., Cuesta, C. E., and Zdun, U. (2023). Architecting digital twins using a domain-driven design-based approach. In 2023 IEEE 20th International Conference on Software Architecture (ICSA), pages 153–163. IEEE.
Mihai, S., Yaqoob, M., Hung, D. V., Davis, W., Towakel, P., Raza, M., Karamanoglu, M., Barn, B., Shetve, D., Prasad, R. V., et al. (2022). Digital twins: A survey on enabling technologies, challenges, trends and future prospects. IEEE Communications Surveys & Tutorials, 24(4):2255–2291.
Minerva, R., Lee, G. M., and Crespi, N. (2020). Digital twin in the iot context: A survey on technical features, scenarios, and architectural models. Proceedings of the IEEE, 108(10):1785–1824.
Moin, A., Rössler, S., and Günnemann, S. (2020). Thingml+ augmenting model-driven software engineering for the internet of things with machine learning. arXiv preprint arXiv:2009.10633.
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., and Bakiras, S. (2021). The role of ai, machine learning, and big data in digital twinning: A systematic literature review, challenges, and opportunities. IEEE Access, 9:32030–32052.
Segovia, M. and Garcia-Alfaro, J. (2022). Design, modeling and implementation of digital twins. Sensors, 22(14):5396.
Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., and Calinescu, A. (2022). Digital twins: State of the art theory and practice, challenges, and open research questions. Journal of Industrial Information Integration, 30:100383.
Stadtmann, F., Rasheed, A., Kvamsdal, T., Johannessen, K. A., San, O., Kölle, K., Tande, J. O., Barstad, I., Benhamou, A., Brathaug, T., et al. (2023). Digital twins in wind energy: Emerging technologies and industry-informed future directions. IEEE Access.
Stahl, T., Völter, M., and Czarnecki, K. (2006). Model-driven software development: technology, engineering, management. John Wiley & Sons, Inc.
Vale, S., Reddy, S., Subramanian, S., Chaudhuri, S. R., Nistala, S. H., Deodhar, A., and Runkana, V. (2023). A model-driven approach for knowledge-based engineering of industrial digital twins. In 2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS), pages 13–23. IEEE.
Wang, H., Chen, X., Jia, F., and Cheng, X. (2023). Digital twin-supported smart city: Status, challenges and future research directions. Expert Systems with Applications, 217:119531.
Publicado
12/05/2025
Como Citar
BARRIGA, Arturo.
Model-Driven Software Engineering to Foster the Adoption of Digital Twins. In: CONGRESSO IBERO-AMERICANO EM ENGENHARIA DE SOFTWARE (CIBSE), 28. , 2025, Ciudad Real/Espanha.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 265-272.
DOI: https://doi.org/10.5753/cibse.2025.35312.
