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Comparison of Static Analysis Architecture Recovery Tools for Microservice Applications

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abstract

Architecture recovery tools help software engineers obtain an overview of the structure of their software systems during all phases of the software development life cycle. This is especially important for microservice applications because they consist of multiple interacting microservices, which makes it more challenging to oversee the architecture. Various tools and techniques for architecture recovery (also called architecture reconstruction) have been presented in academic and gray literature sources, but no overview and comparison of their accuracy exists. This paper presents the results of a multivocal literature review with the goal of identifying architecture recovery tools for microservice applications and a comparison of the identified tools' architectural recovery accuracy. We focused on static tools since they can be integrated into fast-paced CI/CD pipelines. 13 such tools were identified from the literature and nine of them could be executed and compared on their capability of detecting different system characteristics. The best-performing tool exhibited an overall F1-score of 0.86. Additionally, the possibility of combining multiple tools to increase the recovery correctness was investigated, yielding a combination of four individual tools that achieves an F1-score of 0.91. Registered report: The methodology of this study has been peer-reviewed and accepted as a registered report at MSR'24: arXiv:2403.06941

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2025 1

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representative citing papers

Network Centrality as a New Perspective on Microservice Architecture

cs.SE · 2025-01-23 · conditional · novelty 5.0

Centrality metrics calculated on service dependency graphs are only weakly to moderately correlated with traditional size, complexity, and quality metrics across 53 microservices, suggesting they capture a distinct architectural perspective.

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  • Network Centrality as a New Perspective on Microservice Architecture cs.SE · 2025-01-23 · conditional · none · ref 21 · internal anchor

    Centrality metrics calculated on service dependency graphs are only weakly to moderately correlated with traditional size, complexity, and quality metrics across 53 microservices, suggesting they capture a distinct architectural perspective.