Survey on Tools and Techniques Detecting Microservice API Patterns
Alexander Bakhtin, Abdullah Al Maruf, Tomas Cerny, Davide Taibi

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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoftware System Performance and Reliability · Cloud Computing and Resource Management · Caching and Content Delivery
