A Feature Table approach to decomposing monolithic applications into microservices

TL;DR

This paper introduces the Feature Table approach, a structured method for decomposing monolithic applications into microservices using feature correlation, rules, and semi-automatic analysis, validated through a case study on Cargo Tracking System.

Contribution

The paper presents a novel structured approach with Feature Cards, Decomposition Rules, and a Feature Table Analysis Tool for effective microservice decomposition.

Findings

More reasonable microservice candidates identified

Feasible implementation with semi-automatic support

Improved metrics compared to related methods

Abstract

Microservice architecture refers to the use of numerous small-scale and independently deployed services, instead of encapsulating all functions into one monolith. It has been a challenge in software engineering to decompose a monolithic system into smaller parts. In this paper, we propose the Feature Table approach, a structured approach to service decomposition based on the correlation between functional features and microservices: (1) we defined the concept of {\em Feature Cards} and 12 instances of such cards; (2) we formulated {\em Decomposition Rules} to decompose monolithic applications; (3) we designed the {\em Feature Table Analysis Tool} to provide semi-automatic analysis for identification of microservices; and (4) we formulated {\em Mapping Rules} to help developers implement microservice candidates. We performed a case study on Cargo Tracking System to validate our microservice-oriented decomposition approach. Cargo Tracking System is a typical case that has been decomposed by other related methods (dataflow-driven approach, Service Cutter, and API Analysis). Through comparison with the related methods in terms of specific coupling and cohesion metrics, the results show that the proposed Feature Table approach can deliver more reasonable microservice candidates, which are feasible in implementation with semi-automatic support.