  Cloud-native systems represent a significant leap in constructing scalable,
large systems, employing microservice architecture as a key element in
developing distributed systems through self-contained components. However, the
decentralized nature of these systems, characterized by separate source codes
and deployments, introduces challenges in assessing system qualities.
Microservice-based systems, with their inherent complexity and the need for
coordinated changes across multiple microservices, lack established best
practices and guidelines, leading to difficulties in constructing and
comprehending the holistic system view. This gap can result in performance
degradation and increased maintenance costs, potentially requiring system
refactoring. The main goal of this project is to offer maintainability
assurance for microservice practitioners. It introduces an automated assessment
framework tailored to microservice architecture, enhancing practitioners'
understanding and analytical capabilities of the multiple system perspectives.
The framework addresses various granularity levels, from artifacts to
constructing holistic views of static and dynamic system characteristics. It
integrates diverse perspectives, encompassing human-centric elements like
architectural visualization and automated evaluations, including coupling
detection, testing coverage measurement, and semantic clone identification.
Validation studies involving practitioners demonstrate the framework's
effectiveness in addressing diverse quality and maintainability issues,
revealing insights not apparent when analyzing individual microservices in
isolation.
