Automated Extraction of Microservice Architecture Using a Rule-Based Approach

Microservices offer a modular approach to software architecture, enhancing flexibility and scalability. This paper introduces an automated extraction method for evaluating microservices' cohesion, complexity, and granularity. Leveraging a rule-based approach, the system identifies methods within a microservice architecture. Metrics such as Average Lack of Cohesion Metric (ALCOM), Number of Operations (NOO), and Average Service Granularity Metric (ASGM) are calculated to assess the extracted microservices. A case study in Account Payyable Microservice of ERP System illustrates the effectiveness of this method in identifying microservice variables and evaluating architecture quality. This research found that the value of ALCOM is −0.93, NOO is 3.63, and ASGM is 0.50.