GreenMicro: Identifying Microservices From Use Cases in Greenfield Development

Microservices architecture is a new paradigm for developing a software system as a collection of independent services that communicate via lightweight protocols. In greenfield development, identifying the microservices is not a trivial task, as there is no legacy code lying around and no old develop...

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Bibliographic Details
Published in:IEEE access 2022, Vol.10, p.67008-67018
Main Authors: Bajaj, Deepali, Goel, Anita, Gupta, S. C.
Format: Article
Language:English
Subjects:
Applications programs
architectural restructuring
Architecture
Automatic decomposition
Benchmark testing
Business
Computer architecture
Decision analysis
Design analysis
Green products
greenfield development
Microservice architectures
microservices
migration
Quality assessment
Requirements analysis
Software
Software engineering
Unified modeling language
use cases
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Summary:Microservices architecture is a new paradigm for developing a software system as a collection of independent services that communicate via lightweight protocols. In greenfield development, identifying the microservices is not a trivial task, as there is no legacy code lying around and no old development to start with. Thus, identification of microservices from requirements becomes an important decision during the analysis and design phase. Use cases play a vital role in the requirements analysis modeling phases in a model-driven software engineering process. Use cases capture the high-level user functions and the scope of system. In this paper, we propose GreenMicro, an automatic microservice identification technique that utilizes the use cases model and the database entities. Both features are the artifacts of analysis and design phase that depict complete functionality of an overall system. In essence, a collection of related use cases indicates a bounded context of the system that can be grouped in a suitable way as microservices. Therefore, our approach GreenMicro clusters close-knit use cases to recover meaningful microservices. We investigate and validate our approach on an in-house proprietary web application and three sample benchmark applications. We have mapped our approach to the state-of-the-art software quality assessment attributes and have presented the results. Preliminary results are motivating and the proposed methodology works as anticipated in identifying functionally cohesive and loosely coupled microservice candidate recommendations. Our approach enables the system architects to identify microservice candidates at an early analysis and design phase of development.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2022.3182495