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Fostering Microservice Maintainability Assurance through a Comprehensive Framework (2407.16873v1)

Published 23 Jul 2024 in cs.SE

Abstract: 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.

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Summary

  • The paper presents a novel automated framework that identifies dependencies in cloud-native microservices and enhances holistic system assessments.
  • It employs rigorous methodologies including literature reviews, static/dynamic analyses, and coding techniques to evaluate architecture quality.
  • The study demonstrates improved maintainability with an AR-based visualization tool that simplifies complex dependency structures.

Fostering Microservice Maintainability Assurance through a Comprehensive Framework

The research conducted by Amr S. Abdelfattah proposes a novel approach to address the challenges associated with maintaining microservice architectures in cloud-native systems. These systems, while offering scalability and efficiency, pose significant challenges due to their decentralized and complex nature. The paper introduces an automated assessment framework designed to enhance the maintainability of microservices by providing a comprehensive understanding of the system architecture.

Core Objectives and Research Questions

The framework aims to tackle several key challenges in microservice architecture: the identification of dependencies, the creation of holistic system views, the implementation of automated testability and quality assessments, and the design of innovative visualization techniques. Four research questions guide the paper: identifying dependencies in microservice systems, constructing system-centric views of architectures, implementing automatic quality assessments, and designing tailored visualization methodologies to effectively communicate systems' constructs to practitioners.

  1. Dependency Identification: The research acknowledges the distributed and heterogeneous nature of dependencies in microservices, proposing a taxonomy to categorize and understand them. This is achieved through a systematic literature review and coding methodologies, facilitating better maintainability insights.
  2. System-Centric Views: The paper emphasizes the need to develop holistic views of microservice systems, allowing teams to understand the architecture’s interdependencies and potential impacts of changes. By employing static and dynamic analyses, the paper creates a comprehensive architecture representation.
  3. Automated Assessment: The absence of tailored quality assessment metrics in microservice systems is addressed by formulating and implementing automatic testability and quality evaluation methods. These assessments provide crucial feedback on maintainability metrics, including endpoint test coverage.
  4. Visualization Methodologies: The research highlights the need for innovative visualization methodologies. It proposes a tailored approach through tools like Microvision, which employs Augmented Reality (AR) to offer an interactive and comprehensive view of microservice architectures.

Methodologies and Findings

The methodologies employed are diverse and systematic, including rigorous literature reviews, Open and Axial coding, systematic architecture reconstruction, and controlled experiments for visualization. These approaches facilitate an evidence-based exploration of the research questions, allowing practitioners to gain insights into dependencies and system behavior.

The paper's findings indicate substantial improvements in understanding microservice systems' maintainability through the proposed framework. Specifically, the dependency matrix provides a clear central viewpoint, and the AR-based visualization tool significantly enhances usability for complex systems. Demonstrated through prototypes and case studies, these methodologies prove effective in tackling the intricacies of microservice ecosystem analysis.

Implications and Future Research

Abdelfattah's research contributes significantly toward improving microservice system maintainability by offering a structured framework that integrates best practices for architecture analysis. The theoretical implications suggest that more nuanced understandings of dependencies and holistic views can lead to improved decision-making and management processes within microservice ecosystems.

Practically, the framework enables practitioners to conduct effective assessments, ensuring the system's robust performance and scalability. The introduction of AR tools in visualizing architectures marks a promising avenue for augmenting traditional software engineering practices.

Future research could explore further advancements in dynamic visualization techniques, integration of evolutionary system aspects through advanced co-change analysis, and more comprehensive applications in interactive documentation and architecture monitoring. The pursuit of these directions could augment the framework's applicability and impact within the field of microservice maintainability.

Through a thorough investigation and presentation of the challenges and methodologies associated with microservice maintainability, this paper provides a substantive foundation for both practical applications and future research endeavors.

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