Microservice Architecture Reconstruction and Visualization Techniques: A Review

July 06, 2022 ยท The Cartographer ยท ๐Ÿ› International Symposium on Service Oriented Software Engineering

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: Microservice Architecture Reconstruction and Visualization Techniques: A Review"

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Authors Tomas Cerny, Amr S. Abdelfattah, Vincent Bushong, Abdullah Al Maruf, Davide Taibi arXiv ID 2207.02988 Category cs.SE: Software Engineering Citations 65 Venue International Symposium on Service Oriented Software Engineering Last Checked 1 day ago
Abstract
Microservice system solutions are driving digital transformation; however, fundamental tools and system perspectives are missing to better observe, understand, and manage these systems, their properties, and their dependencies. Microservices architecture leads towards decentralization, which implies many advantages to system operation; it, however, brings challenges to their development. Microservice systems often lack a system-centric perspective that would help engineers better cope with system evolution and quality assessment. In this work, we explored microservice-specific architecture reconstruction based on static analysis. Such reconstruction typically results in system models to visualize selected system-centric perspectives. Conventional models involve 2D methods; however, these methods are limited in utility when services proliferate. We considered various architectural perspectives relevant to microservices and assessed the relevancy of the traditional method, comparing it to alternative data visualization using 3D space. As a representative of the 3D method, we considered a 3D graph model presented in augmented reality. To begin testing the feasibility of deriving such perspectives from microservice systems, we developed and implemented prototype tools for software architecture reconstruction and visualization of compared perspectives. Using these prototypes, we performed a small user study with software practitioners to highlight the potentials and limitations of these innovative visualizations used for common practitioner reasoning and tasks.
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