ModARO: A Modular Approach to Architecture Reconstruction of Distributed Microservice Codebases

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Authors: Oscar Manglaras, Alex Farkas, Thomas Woolford, Christoph Treude, Markus Wagner
Cited by: 0

Abstract

Microservice architectures promote small, independently developed services, but increase overall architectural complexity. It is crucial that developers understand the architecture and how changes to a service affect the overall system, but rapid and independent development of services increases the risk of architectural drift and discourages the creation and maintenance of documentation. Automatic architecture reconstruction can help avoid these issues, but it is difficult to reuse reconstruction code across multiple projects, as all use different combinations of technologies and project-specific conventions. Reconstruction of architecture-level details is further complicated by the tendency to split microservices into separate repositories, preventing a full view of the system from any one codebase. In this paper, we present and evaluate ModARO, an approach to microservice architecture reconstruction that allows writing modular reconstruction code ('extractors') for any technologies and reusing them across different projects, independent of the surrounding technology stack or whether or not the services are split into multiple codebases. We demonstrate the effectiveness of our approach by configuring ModARO to reconstruct 10 open source projects, and we validate the usefulness and usability of ModARO against a state-of-the-art baseline in a user study with 8 industry practitioners. Using this approach, developers can assemble or create extractors tailored to their technology stacks and distribute architecture reconstruction across repositories, enabling integration into repository CI/CD pipelines.

Fields of Study & Subjects

Software Engineering Research Software System Performance and Reliability Advanced Software Engineering Methodologies

Publication details

Journal / source
arXiv (Cornell University)
Publication date
9 February 2026
Language
EN
Document type
Preprint