Novel automated method identifies candidate microservices in monolithic applications, suggesting improved migration efficiency.
Introduction:The software industry has increasingly transitioned from Monolithic Architecture (MA) to Microservices Architecture (MSA) due to the significant advantages offered by MSA. A crucial first step in this migration process is the identification of suitable microservices.Novelty Statement:This work aims to introduce an automated method for more effectively identifying potential microservices within monolithic applications.Materials and Methods:Our approach leverages the source code to construct a frequency-based class dependency graph through graph analysis techniques. A clustering algorithm is then applied to this graph to identify optimal candidate microservices.Results and Discussion:We evaluate the effectiveness of the proposed approach using several metrics, including the number of microservices, Newman-Girvan Modularity (NGM), and F1-Score. The results demonstrate that the approach accurately identifies candidate microservices, achieving an average F1 score of 0.88 and an average NGM score of 0.526.Concluding Remarks:The proposed approach proves to be an effective tool for assisting developers in migrating from MA to MSA, facilitating a more streamlined transition process.
No takes yet. Share an insight, caveat, or question.
Kayani et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: