Migration to Microservices: A Comparative Study of Decomposition Strategies and Analysis Metrics

• URL: http://arxiv.org/abs/2402.08481v1
• Date: Tue, 13 Feb 2024 14:15:00 GMT
• Title: Migration to Microservices: A Comparative Study of Decomposition Strategies and Analysis Metrics
• Authors: Meryam chaieb, Mohamed Aymen Saied
• Abstract summary: We present a novel clustering method to identify potential in a given monolithic application. Our approach employs a density-based clustering algorithm considering static analysis, structural, and semantic relationships between classes.
• Score: 0.5076419064097734
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The microservices architectural style is widely favored for its scalability, reusability, and easy maintainability, prompting increased adoption by developers. However, transitioning from a monolithic to a microservices-based architecture is intricate and costly. In response, we present a novel method utilizing clustering to identify potential microservices in a given monolithic application. Our approach employs a density-based clustering algorithm considering static analysis, structural, and semantic relationships between classes, ensuring a functionally and contextually coherent partitioning. To assess the reliability of our microservice suggestion approach, we conducted an in-depth analysis of hyperparameter sensitivity and compared it with two established clustering algorithms. A comprehensive comparative analysis involved seven applications, evaluating against six baselines, utilizing a dataset of four open-source Java projects. Metrics assessed the quality of generated microservices. Furthermore, we meticulously compared our suggested microservices with manually identified ones in three microservices-based applications. This comparison provided a nuanced understanding of our approach's efficacy and reliability. Our methodology demonstrated promising outcomes, showcasing remarkable effectiveness and commendable stability.

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