Using LLMs to support architectural decision-making in IoT systems
Resumo
A IoT conecta dispositivos físicos, permitindo comunicação e automação em diversas áreas. No entanto, muitos sistemas de IoT falham em atender aos requisitos esperados, pois são sistemas complexos. Arquiteturas de Referência oferecem uma base comum para o desenvolvimento desses sistemas, promovendo consistência. Este artigo apresenta uma proposta de tese que se concentra na criação sistematizada de uma AR para IoT, utilizando métodos ProSA-AR, e no desenvolvimento e validação de mecanismos de instanciação e mecanismos de atualização. O objetivo é oferecer suporte para arquitetos de software, aumentando a eficiência e a qualidade no desenvolvimento de sistemas de IoT. Link vídeo: https://youtu.be/sPb1OUn3Wzo
Referências
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Cervantes, H., Kazman, R., and Cai, Y. (2025). An llm-assisted approach to designing software architectures using add.
Graciano Neto, V. V., Garcés, L., Guessi, M., de Oliveira, L. B. R., and Oquendo, F. (2015). On the equivalence between reference architectures and metamodels. In Proceedings of the 1st International Workshop on Exploring Component-Based Techniques for Constructing Reference Architectures, CobRA ’15, page 21–24, New York, NY, USA. Association for Computing Machinery.
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Nascimento, R., Santos, V., Carvalho, B., Correia, J., Rivero, L., Santos, R., Silva, F., Teles, A., and Viana, D. (2023). Sysiotml: A technique for modeling applications in the context of iot. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS, pages 187–194. INSTICC, SciTePress.
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Saemaldahr, R., Thapa, B., Maikoo, K., and Fernandez, E. B. (2021). Reference architectures for the iot: A survey. In Saeed, F., Mohammed, F., and Al-Nahari, A., editors, Innovative Systems for Intelligent Health Informatics, pages 635–646, Cham. Springer International Publishing.
Shinde, P. P. and Shah, S. (2018). A review of machine learning and deep learning applications. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), pages 1–6.
Sisodia, D., Li, J., Mergendahl, S., and Cam, H. (2024). A two-mode, adaptive security framework for smart home security applications. ACM Trans. Internet Things, 5(2).
Steinmacher, I., Penney, J. M., Felizardo, K. R., Garcia, A. F., and Gerosa, M. A. (2024). Can chatgpt emulate humans in software engineering surveys? In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM ’24, page 414–419, New York, NY, USA. Association for Computing Machinery.
Tiwari, N., Pandey, A., and Kokala, A. (2025). Challenges and solutions for countering emerging security threats to iot devices. International Journal of Experimental Research and Review, 47:59–68.
Trinkenreich, B., Calefato, F., Hanssen, G., Blincoe, K., Kalinowski, M., Pezzè, M., Tell, P., and Storey, M.-A. (2025). Get on the train or be left on the station: Using llms for software engineering research.
Ystgaard, K., Atzori, L., Palma, D., Heegaard, P., Bertheussen, L., Jensen, M., and De Moor, K. (2023). Review of the theory, principles, and design requirements of human-centric internet of things (iot). Journal of Ambient Intelligence and Humanized Computing, 14:1–33.
Zimmermann, A., Schmidt, R., Sandkuhl, K., Jugel, D., Bogner, J., and Möhring, M. (2017). Decision management for micro-granular digital architecture. In 2017 IEEE 21st International Enterprise Distributed Object Computing Workshop (EDOCW), pages 29–38.
Zimmermann, A., Schmidt, R., Sandkuhl, K., Wißotzki, M., Jugel, D., and Möhring, M. (2015). Digital enterprise architecture - transformation for the internet of things. In 2015 IEEE 19th International Enterprise Distributed Object Computing Workshop, pages 130–138.
Bakiris, E., Papadakis, N., Katsarou, V., and Alampasis, N. (2024). Septon toolkit application: An overview of the security techniques used from wearable medical devices to physician’s healthcare platform. In Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA ’24, page 582–586, New York, NY, USA. Association for Computing Machinery.
Barros, C., Azevedo, B., Graciano Neto, V., Kassab, M., Kalinowski, M., Nascimento, H., and Bandeira, M. (2024). Large language model for qualitative research – a systematic mapping study.
Benotmane, M., Elhari, K., and Kabbaj, A. (2022). Meta-comparison of iot reference architectures and models. In Kacprzyk, J., Balas, V. E., and Ezziyyani, M., editors, Advanced Intelligent Systems for Sustainable Development (AI2SD’2020), pages 337–357, Cham. Springer International Publishing.
Cavalcante, E., Alves, M. P., Batista, T., Delicato, F. C., and Pires, P. F. (2015). An analysis of reference architectures for the internet of things. In Proceedings of the 1st International Workshop on Exploring Component-Based Techniques for Constructing Reference Architectures, CobRA ’15, page 13–16, New York, NY, USA. Association for Computing Machinery.
Cervantes, H., Kazman, R., and Cai, Y. (2025). An llm-assisted approach to designing software architectures using add.
Graciano Neto, V. V., Garcés, L., Guessi, M., de Oliveira, L. B. R., and Oquendo, F. (2015). On the equivalence between reference architectures and metamodels. In Proceedings of the 1st International Workshop on Exploring Component-Based Techniques for Constructing Reference Architectures, CobRA ’15, page 21–24, New York, NY, USA. Association for Computing Machinery.
Gräßler, I., Preuß, D., Brandt, L., and Mohr, M. (2022). Efficient extraction of technical requirements applying data augmentation. In 2022 IEEE International Symposium on Systems Engineering (ISSE), pages 1–8.
Hou, X., Zhao, Y., Liu, Y., Yang, Z., Wang, K., Li, L., Luo, X., Lo, D., Grundy, J., and Wang, H. (2024). Large language models for software engineering: A systematic literature review.
Motta, R. C., de Oliveira, K. M., and Travassos, G. H. (2018). On challenges in engineering iot software systems. In Proceedings of the XXXII Brazilian Symposium on Software Engineering, SBES ’18, page 42–51, New York, NY, USA. Association for Computing Machinery.
Moura, D. L. L., Aquino, A. L. L., and Loureiro, A. A. F. (2023). On the integration of ledger technology and edge computing for intelligent transportation systems. In Proceedings of the Int’l ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks, PE-WASUN ’23, page 9–16, New York, NY, USA. Association for Computing Machinery.
Nakagawa, E. Y. and Antonino, P. O. (2023). An Overview of Reference Architectures, pages 5–15. Springer International Publishing, Cham.
Nakagawa, E. Y., Guessi, M., Maldonado, J. C., Feitosa, D., and Oquendo, F. (2014). Consolidating a process for the design, representation, and evaluation of reference architectures. In 2014 IEEE/IFIP Conference on Software Architecture, pages 143–152.
Nascimento, R., Santos, V., Carvalho, B., Correia, J., Rivero, L., Santos, R., Silva, F., Teles, A., and Viana, D. (2023). Sysiotml: A technique for modeling applications in the context of iot. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS, pages 187–194. INSTICC, SciTePress.
Nižetić, S., Šolić, P., López-de-Ipiña González-de-Artaza, D., and Patrono, L. (2020). Internet of things (iot): Opportunities, issues and challenges towards a smart and sustainable future. Journal of Cleaner Production, 274:122877.
Paes, C. and Neto, V. G. (2023). Sosml: Rumo a uma linguagem de modelagem arquitetural para sistemas-de-sistemas intensivos em software. In Anais do V Workshop em Modelagem e Simulação de Sistemas Intensivos em Software, pages 61–65, Porto Alegre, RS, Brasil. SBC.
Rincy, T. and Gupta, R. (2020). A survey on machine learning approaches and its techniques:. In 2020 IEEE International Students’ Conference on Electrical,Electronics and Computer Science (SCEECS), pages 1–6.
Saemaldahr, R., Thapa, B., Maikoo, K., and Fernandez, E. B. (2021). Reference architectures for the iot: A survey. In Saeed, F., Mohammed, F., and Al-Nahari, A., editors, Innovative Systems for Intelligent Health Informatics, pages 635–646, Cham. Springer International Publishing.
Shinde, P. P. and Shah, S. (2018). A review of machine learning and deep learning applications. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), pages 1–6.
Sisodia, D., Li, J., Mergendahl, S., and Cam, H. (2024). A two-mode, adaptive security framework for smart home security applications. ACM Trans. Internet Things, 5(2).
Steinmacher, I., Penney, J. M., Felizardo, K. R., Garcia, A. F., and Gerosa, M. A. (2024). Can chatgpt emulate humans in software engineering surveys? In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM ’24, page 414–419, New York, NY, USA. Association for Computing Machinery.
Tiwari, N., Pandey, A., and Kokala, A. (2025). Challenges and solutions for countering emerging security threats to iot devices. International Journal of Experimental Research and Review, 47:59–68.
Trinkenreich, B., Calefato, F., Hanssen, G., Blincoe, K., Kalinowski, M., Pezzè, M., Tell, P., and Storey, M.-A. (2025). Get on the train or be left on the station: Using llms for software engineering research.
Ystgaard, K., Atzori, L., Palma, D., Heegaard, P., Bertheussen, L., Jensen, M., and De Moor, K. (2023). Review of the theory, principles, and design requirements of human-centric internet of things (iot). Journal of Ambient Intelligence and Humanized Computing, 14:1–33.
Zimmermann, A., Schmidt, R., Sandkuhl, K., Jugel, D., Bogner, J., and Möhring, M. (2017). Decision management for micro-granular digital architecture. In 2017 IEEE 21st International Enterprise Distributed Object Computing Workshop (EDOCW), pages 29–38.
Zimmermann, A., Schmidt, R., Sandkuhl, K., Wißotzki, M., Jugel, D., and Möhring, M. (2015). Digital enterprise architecture - transformation for the internet of things. In 2015 IEEE 19th International Enterprise Distributed Object Computing Workshop, pages 130–138.
Publicado
04/11/2025
Como Citar
NASCIMENTO, Rodrigo; AVELINO, Guilherme; VIANA, Davi.
Using LLMs to support architectural decision-making in IoT systems. In: WORKSHOP DE TESES E DISSERTAÇÕES EM QUALIDADE DE SOFTWARE - SIMPÓSIO BRASILEIRO DE QUALIDADE DE SOFTWARE (SBQS), 24. , 2025, São José dos Campos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 15-22.
DOI: https://doi.org/10.5753/sbqs_estendido.2025.15835.
