Distributed Architecture Reconstruction of Polyglot and Multi-Repository Microservice Projects

2026-02-08

AI Summary

This work addresses the challenge of maintaining up-to-date architectural documentation in microservice systems, which is exacerbated by polyglot implementations, multiple repositories, and rapid independent evolution. Existing static refactoring approaches are often limited to single-repository settings or homogeneous technology stacks. To overcome these limitations, we propose a distributed static architecture reconstruction framework that supports multi-language and multi-repository environments. The framework employs pluggable extractor modules for language-specific analysis and introduces mechanisms for cross-repository data propagation and fusion, enabling seamless interoperability with existing static analysis tools. To the best of our knowledge, this is the first framework to enable distributed, collaborative architecture reconstruction, significantly enhancing the scalability and usability of automated documentation generation and maintenance in complex microservice ecosystems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Agent/AI Theories and Architectures
• Natural Language Processing: Machine Translation, Multilinguality, Cross-Lingual NLP

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

Microservice architectures encourage the use of small, independently developed services; however, this can lead to increased architectural complexity. Accurate documentation is crucial, but is challenging to maintain due to the rapid, independent evolution of services. While static architecture reconstruction provides a way to maintain up-to-date documentation, existing approaches suffer from technology limitations, mono-repo constraints, or high implementation barriers. This paper presents a novel framework for static architecture reconstruction that supports technology-specific analysis modules, called \emph{extractors}, and supports \emph{distributed architecture reconstruction} in multi-repo environments. We describe the core design concepts and algorithms that govern how extractors are executed, how data is passed between them, and how their outputs are unified. Furthermore, the framework is interoperable with existing static analysis tools and algorithms, allowing them to be invoked from or embedded within extractors.

Problem

• microservice
• architecture reconstruction
• polyglot
• multi-repository
• static analysis

Innovation

• distributed architecture reconstruction
• microservice
• polyglot
• multi-repository
• static analysis