Recovery of Anti-Patterns from Microservices

Abstract

Microservices have brought an evolution in the Service Oriented Architecture by introducing high independence at various levels. These services provide independent development, service to service communication, individual database per service, independent deployment, and maintenance, etc. The service-oriented systems support the quick implementation of customized changes to software applications. These frequent changes might result in introducing some feeble solutions. These solutions commonly known as “Anti-Patterns”, can negatively impact the quality of the microservices. Another reason for anti-patterns occurrence may be due to the migration of software applications developed on monolithic architecture to microservices architecture. This process demands a high knowledge of microservices-based design patterns and best practices to avoid flaws that might instigate while migration from centralized to a distributed environment. In this research, we have selected 18 microservices related anti-patterns and proposed an approach for their detection. We found only a single approach that presented an algorithm to detect microservices specific Anti-Patterns [1]; the study focused on detecting five anti-patterns. However, our proposed approach differs from the state-of-the-art approach, as, firstly, we focused on the detection of a large number of anti-patterns. Secondly, we have implemented reverse engineering on microservices-based systems and then detected anti-patterns from these systems. Our research focuses on the detection of microservices specific anti-patterns from microservices-based software applications. Our approach is developed as an automated approach supplemented with an add-in for Sparx System EA for the automatic detection of anti-patterns from microservices-based systems. We have evaluated our approach using precision and recall metrics