Survey on Tools and Techniques Detecting Microservice API Patterns

TL;DR

This survey reviews existing tools and techniques for detecting microservice API patterns, highlighting gaps and opportunities for enhancing quality assessment in microservice architectures.

Contribution

It catalogs current tools for MAP detection, analyzes their mechanisms, and identifies areas for improvement and future research directions.

Findings

Many MAP detection tools are limited in scope.

Significant gaps exist in current quality assessment tools.

Opportunities for developing more comprehensive detection techniques.

Abstract

It is well recognized that design patterns improve system development and maintenance in many aspects. While we commonly recognize these patterns in monolithic systems, many patterns emerged for cloud computing, specifically microservices. Unfortunately, while various patterns have been proposed, available quality assessment tools often do not recognize many. This article performs a grey literature review to find and catalog available tools to detect microservice API patterns (MAP). It reasons about mechanisms that can be used to detect these patterns. Furthermore, the results indicate gaps and opportunities for improvements for quality assessment tools. Finally, the reader is provided with a route map to detection techniques that can be used to mine MAPs.