Articles
| Open Access | The Evolution of Software Engineering Paradigms: From Monolithic Architectures To AI-Augmented Autonomous Ecosystems
Erica Sundown , Department of Computer Science and Software Systems, University of Edinburgh, United KingdomAbstract
This research article provides an exhaustive examination of the transformative shifts currently redefining the field of software engineering. By synthesizing decades of architectural evolution with the contemporary emergence of Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs), the study delineates the transition from traditional monolithic systems to decentralized, service-oriented, and cloud-native architectures. The investigation explores the critical role of microservices migration, the complexities of distributed software development, and the burgeoning influence of multi-agent systems in automating the software development life cycle. Furthermore, the article addresses the pedagogical implications of conversational AI in software engineering education and the necessity for rigorous experimental validation in an era of rapid technological disruption. Through a detailed analysis of software ecosystems, model-driven development, and AI-augmented refactoring frameworks, this research establishes a comprehensive roadmap for architecting the future of software engineering. The findings suggest that while AI significantly enhances productivity and requirements engineering, it introduces novel challenges regarding creativity, software quality, and systemic complexity that require a fundamental re-evaluation of established engineering principles.
Keywords
Software Engineering, Large Language Models, Microservices Migration, Generative AI
References
Carleton, F. Shull, and E. Harper, “Architecting the Future of Software Engineering,” Computer 55, no. 9 (2022): 89–93, https://doi.org/10.1109/MC.2022.3187912 .
S. Jansen, A. Finkelstein, and S. Brinkkemper, “A Sense of Community: A Research Agenda for Software Ecosystems,” in Proceedings of the 2009 31st International Conference on Software Engineering - Companion Volume (2009–05) (IEEE Computer Society, 2009), 187–190, https://doi.org/10.1109/ICSE-COMPANION.2009.5070978.
Sengupta, S. Chandra, and V. Sinha, “A Research Agenda for Distributed Software Development,” in Proceedings of the 28th International Conference on Software Engineering (New York, NY, USA, 2006-05-28) (ICSE ‘06) (Association for Computing Machinery, 2006), 731–740, https://doi.org/10.1145/1134285.1134402.
J. Bosch, H. H. Olsson, and I. Crnkovic, “Engineering AI Systems: A Research Agenda,” in Artificial Intelligence Paradigms for Smart Cyber-Physical Systems (IGI Global, 2021), 1–19, https://doi.org/10.4018/978-1-7998-5101-1.ch001.
Sriram and A. Khajeh-Hosseini, “Research Agenda in Cloud Technologies,” 2010, https://doi.org/10.48550/arXiv.1001.3259.
M. P. Papazoglou, P. Traverso, S. Dustdar, and F. Leymann, “Service-Oriented Computing: A Research Roadmap,” International Journal of Cooperative Information Systems 17, no. 2 (2008): 223–255, https://doi.org/10.1142/S0218843008001816.
V. Jackson, B. Vasilescu, D. Russo, et al., “Creativity, Generative AI, and Software Development: A Research Agenda,” 2024, arXiv:2406.01966 [cs], https://doi.org/10.48550/arXiv.2406.01966.
Fan, B. Gokkaya, M. Harman, et al., “Large Language Models for Software Engineering: Survey and Open Problems,” in Proceedings of the 2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE) (IEEE, 2023), 31–53, https://doi.org/10.1109/ICSE-FoSE59343.2023.00008.
Cheng, J. H. Husen, L. Yijun, et al., “Generative AI for Requirements Engineering: A Systematic Literature,” Review (2025), arXiv:2409.06741 [cs], https://doi.org/10.48550/arXiv.2409.06741.
He, C. Treude, and D. Lo, “LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead,” ACM Transactions on Software Engineering and Methodology 34, no. 5 (2025): 124, https://doi.org/10.1145/3712003.
H. Jin, L. Huang, H. Cai, J. Yan, B. Li, and H. Chen, “From LLMs to LLM-Based Agents for Software Engineering: A Survey of Current,” Challenges and Future (2025), arXiv:2408.02479 [cs], https://doi.org/10.48550/arXiv.2408.02479.
X. Hou, Y. Zhao, Y. Liu, et al., “Large Language Models for Software Engineering: A Systematic Literature Review,” ACM Transactions on Software Engineering and Methodology 33, no. 8 (2024): 220:1–220:79, https://doi.org/10.1145/3695988.
J. Liu, K. Wang, Y. Chen, et al., “Large Language Model-Based Agents for Software Engineering: A Survey,” 2024, arXiv:2409.02977 [cs], https://doi.org/10.48550/arXiv.2409.02977.
Sengul, R. Neykova, and G. Destefanis, “Software Engineering Education in the Era of Conversational AI: Current Trends and Future Directions,” Frontiers in Artificial Intelligence 7 (2024): 1436350, https://doi.org/10.3389/frai.2024.1436350.
Balalaie A, Heydarnoori A, Jamshidi P. Migrating to cloud-native architectures using microservices: an experience report. In European Conference on Service-Oriented and Cloud Computing 2015 Sep 15 (pp. 201-215). Springer, Cham.
Gouigoux JP, Tamzalit D. “Functional-First” Recommendations for Beneficial Microservices Migration and Integration Lessons Learned from an Industrial Experience. In 2019 IEEE International Conference on Software Architecture Companion (ICSA-C) 2019 Mar 25 (pp. 182- 186). IEEE.
Mazzara M, Dragoni N, Bucchiarone A, Giaretta A, Larsen ST, Dustdar S. Microservices: Migration of a mission critical system. IEEE Transactions on Services Computing. 2018 Dec 21.
De Alwis AA, Barros A, Fidge C, Polyvyanyy A. Discovering microservices in enterprise systems using a business object containment heuristic. In OTM Confederated International Conferences” On the Move to Meaningful Internet Systems” 2018 Oct 22 (pp. 60-79). Springer, Cham.
Eski S, Buzluca F. An automatic extraction approach: Transition to microservices architecture from monolithic application. In Proceedings of the 19th International Conference on Agile Software Development: Companion 2018 May 21 (pp. 1-6).
Walter F. Tichy. "Should computer scientists experiment more? 16 reasons to avoid experimentation." IEEE Computer, Vol. 31, No. 5, May 1998.
Marvin V. Zelkowitz and Delores Wallace. Experimental validation in software engineering. Information and Software Technology, Vol 39, no 11, 1997, pp. 735-744.
Marvin V. Zelkowitz and Delores Wallace. Experimental models for validating technology. IEEE Computer, Vol. 31, No. 5, 1998, pp.23-31.
Mary-Claire van Leunen and Richard Lipton. How to have your abstract rejected. acm.org/sigsoft/conferences/vanLeunenLipton.html.
K. S. Hebbar, “An AI-Augmented Framework for Refactoring Enterprise Monolithic Systems,” INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, vol. 11, no.8s, pp. 593-604, July. 2023 https://www.ijisae.org/index.php/IJISAE/article/view/8046/7054
Download and View Statistics
Copyright License
Copyright (c) 2024 Erica Sundown
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.