The transformation of software systems across diverse architectural paradigms represents one of the most pivotal trends in contemporary information technology. This research article systematically explores the evolution of Microsoft’s ASP.NET framework into ASP.NET Core as a microcosm of broader architectural shifts from monolithic systems toward modular, microservice-based designs. Drawing from pivotal frameworks and methodologies in the literature, this article integrates theoretical foundations, empirical insights, and methodological approaches to trace the strategic imperatives, technical challenges, and implementation pathways underlying architectural modernization. It begins by situating ASP.NET Core within the broader context of software engineering evolution and legacy modernization discourse. Methodologically, it employs a comprehensive literature-based analytical synthesis, engaging with diverse studies on legacy migration, microservice identification, decomposition techniques, and architectural assessment frameworks. Results highlight recurring themes of modular decomposition, tooling efficacy, semantic analysis, and strategic alignment between organizational objectives and technological adoption. The discussion extensively interprets these findings, situating them within competing scholarly debates on automation versus manual refactoring, operational complexity versus flexibility trade-offs, and future research trajectories in reinforcement learning and AI-assisted migration. The research contributes to theoretical and practical understandings by situating tool-specific evolution (e.g., ASP.NET to ASP.NET Core) within the larger canon of architectural transformation research, thereby offering a comprehensive foundation for future applied and empirical investigations.

Software architecture evolution, microservices migration, ASP.NET Core, legacy system modernization

Freire, A.F.A.A., Sampaio, A.F., Carvalho, L.H.L., Medeiros, O., & Mendonça, N.C. Migrating production monolithic systems to microservices using aspect oriented programming. Softw. Pract. Exp. 2021, 51, 1280–1307.

Dehghani, M., Kolahdouz-Rahimi, S., Tisi, M., & Tamzalit, D. Facilitating the migration to the microservice architecture via model-driven reverse engineering and reinforcement learning. Softw. Syst. Model. 2022, 21, 1115–1133.

Sellami, K., Ouni, A., Saied, M.A., Bouktif, S., & Mkaouer, M.W. Improving microservices extraction using evolutionary search. Inf. Softw. Technol. 2022, 151, 106996.

Kalia, A.K., Xiao, J., Krishna, R., Sinha, S., Vukovic, M., & Banerjee, D. Mono2Micro: A practical and effective tool for decomposing monolithic Java applications to microservices. In Proceedings of the 29th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Athens, Greece, 18 August 2021; Spinellis, D., Ed.; Association for Computing Machinery: New York, NY, USA, pp. 1214–1224.

Trabelsi, I., Abdellatif, M., Abubaker, A., Moha, N., Mosser, S., & Ebrahimi-Kahou, S. From legacy to microservices: A type-based approach for microservices identification using machine learning and semantic analysis. J. Software: Evol. Process 2022, 35, e2503.

Löhnertz, J., & Oprescu, A.M. Steinmetz: Toward automatic decomposition of monolithic software into microservices. In Proceedings of the CEUR Workshop Proceedings, Uzbekistan, Tashkent, 7–9 October 2020; Constantinou, E., Ed.; CEUR-WS. Volume 2754, pp. 1–8.

Auer, F., Lenarduzzi, V., Felderer, M., & Taibi, D. From monolithic systems to Microservices: An assessment framework. Inf. Softw. Technol. 2021, 137, 106600.

Mazzara, M., Dragoni, N., Bucchiarone, A., Giaretta, A., Larsen, S.T., & Dustdar, S. Microservices: Migration of a Mission Critical System. IEEE Trans. Serv. Comput. 2021, 14, 1464–1477.

Zaragoza, P., Seriai, A.D., Seriai, A., Bouziane, H.L., Shatnawi, A., & Derras, M. Materializing Microservice-oriented Architecture from Monolithic Object-oriented Source Code. Commun. Comput. Inf. Sci. 2022, 1622, 143–168.

Valiveti, S. S. S. Evolution of ASP. NET to ASP. NET Core: Tools, Strategies, and Implementation Approaches. In 2025 IEEE 2nd International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), 2025, pp. 1–7.

Kyryk, M., Tymchenko, O., Pleskanka, N., & Pleskanka, M. Methods and process of service migration from monolithic architecture to microservices. In Proceedings of the 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2022, Lviv-Slavske, Ukraine, 22–26 February 2022; IEEE, pp. 553–558.

Colanzi, T., Amaral, A., Assunção, W., Zavadski, A., Tanno, D., Garcia, A., & Lucena, C. Are we speaking the industry language? The practice and literature of modernizing legacy systems with microservices. In Proceedings of the ACM International Conference Proceeding Series. Association for Computing Machinery, Joinville, Brazil, 5 October 2021; pp. 61–70.

Osman, M.H., Saadbouh, C., Sharif, K.Y., Admodisastro, N., & Basri, M.H. From Monolith to Microservices: A Semi-Automated Approach for Legacy to Modern Architecture Transition using Static Analysis. Int. J. Adv. Comput. Sci. Appl. 2022, 13, 907–916.

Robinson, T., & Zhang, W. Scalability challenges in legacy system migration: Addressing the multi-cloud environment. Journal of Cloud Computing, 27(1), 59–75.

Turner, M., & Kumar, S. Policy implications of legacy system migration in the public sector. Journal of Public Administration Research, 31(4), 112–127.

Brown, T., & Gupta, M. Human factors in legacy system migration: Overcoming resistance to change. Journal of Organizational Behavior, 23(1), 56–72.

Mitchell, R., & Harris, B. Evaluating migration models for legacy systems: An empirical comparison. Journal of Information Technology Research, 11(2), 93–107.

Wang, J., & Chen, Q. Predictive analytics for legacy system modernization. Journal of Artificial Intelligence Research, 38(4), 230–247.

Hughes, M., & Patel, D. Building adaptive strategies for legacy system migration: The role of AI in system modernization. International Journal of AI and Systems Engineering, 14(2), 75–88.

Sharma, P., & Patel, V. A comparative study of migration models in healthcare IT. Journal of Healthcare Information Management, 19(3), 34–50.

Zhao, L., & Tan, W. The role of Agile methodologies in system modernization. International Journal of Software Engineering, 15(3), 88–102.

Roberts, A., & Watson, C. Best practices in legacy system migration: A comprehensive framework. Journal of IT Systems and Management, 16(4), 211–230.

Kim, S., & Zhao, X. Long-term impact of legacy system migration on operational efficiency. Journal of Business and Technology, 20(2), 34–49.

Bell, M., & Johansson, P. The future of IT infrastructure: Legacy system modernization in the digital era. Journal of IT and Digital Transformation, 12(1), 40–55.

Patel, N., & Roberts, D. Risk management in legacy system migration: A data-driven approach. Journal of Systems and Software Engineering, 45(4), 126–145.

Lee, K., & Zhang, T. Holistic approach to legacy system migration: Integrating organizational, operational, and technical data. Journal of Information Systems Research, 28(3), 135–150.

Dube, S., & Gruber, S. Leveraging cloud services for legacy system modernization. Journal of Cloud Solutions, 22(3), 105–120.

Yang, L., & Lee, J. Measuring success in legacy system modernization: A focus on post-migration outcomes. Journal of Technology and Innovation, 18(1), 122–138.

Harris, G., & Singh, R. Incorporating emerging technologies in legacy system modernization. International Journal of Technology Trends, 16(2), 88–104.

Wang, Y.T., Ma, S.P., Lai, Y.J., & Liang, Y.C. Qualitative and quantitative comparison of Spring Cloud and Kubernetes in migrating from a monolithic to a microservice architecture. Serv. Oriented Comput. Appl. 2023, 17, 149–159.

Zaragoza, P., Seriai, A.D., Seriai, A., Bouziane, H.L., Shatnawi, A., & Derras, M. Refactoring monolithic object-oriented source code to materialize microservice-oriented architecture. In Proceedings of the 16th International Conference on Software Technologies, ICSOFT 2021, Virtual Event, 6–8 July 2021; SciTePress: Setúbal, Portugal, pp. 78–89.