microservices

This study addresses the lack of systematic guidance for enterprise software teams in choosing between monolithic and microservices architectures. The work proposes a decision-making framework that integrates technical and organizational factors, evaluating the trade-offs of each architecture across dimensions such as scalability, reliability, deployment efficiency, and organizational complexity. The assessment is grounded in system scale, business requirements, operational maturity, and long-term maintainability. Through architectural pattern analysis, a structured evaluation model, and multiple case studies, the authors develop a practical selection methodology tailored to real-world engineering contexts. This approach offers enterprises clear architectural evolution pathways and actionable guidelines aligned with their developmental stages, thereby significantly enhancing the rationality and sustainability of system design decisions.

Microservices achieve physical isolation but fail to prevent the proliferation of logical coupling, undermining module independence. This paper proposes a novel modularization paradigm based on universal interface boundaries, constructs a quantifiable model for assessing module independence, and designs a runtime mechanism supporting dynamic loading, unloading, and hot updates within a single process. Its core contributions are: (1) reframing module independence as a formal, modelable, and measurable system property—moving beyond qualitative assertions; (2) replacing implicit dependencies with explicit interface contracts to fundamentally block coupling propagation; and (3) implementing the EIGHT platform prototype, which achieves microservice-level module autonomy within a monolithic process. Experimental results demonstrate that the approach significantly reduces the impact scope of cross-module changes, enhancing system maintainability and evolutionary efficiency. It provides both theoretical foundations and practical pathways for next-generation architectures transcending the monolith–microservice dichotomy.

Migrating monolithic systems to microservices faces a critical challenge: the lack of systematic, code-level guidance for identifying and decoupling inter-component dependencies—existing research predominantly addresses architectural concerns while neglecting actionable, refactor-driven practices. To bridge this gap, we propose a code-level refactoring methodology tailored for microservice migration. Our approach introduces the first comprehensive refactoring catalog for migration, comprising seven empirically grounded patterns that address key scenarios—including service boundary identification, cross-service call extraction, and data decoupling. Integrating literature analysis with industrial practice, the method leverages dependency graph analysis, semantics-aware refactoring, and a hierarchical classification strategy to enable standardized and automatable migration. Experimental evaluation demonstrates that our approach significantly reduces refactoring decision complexity, improves service extraction accuracy and long-term maintainability, and delivers the first production-ready, extensible code-level migration framework for microservice evolution.

Microservice system developers lack empirical evidence regarding the types, root causes, and remediation strategies of recurring issues. Method: We adopt a mixed-methods approach—quantitatively analyzing 2,641 open-source issues, qualitatively interviewing 15 practitioners, and conducting a global survey with 150 practitioners. Contribution/Results: We introduce the first comprehensive, domain-specific three-level taxonomy (“Issue–Cause–Solution”) for microservices. We identify five high-frequency issue domains—including technical debt, CI/CD pipeline failures, and exception handling—and three predominant root causes, notably generic programming errors. From our analysis, we distill 177 actionable, context-aware remediation strategies. This work establishes an empirical foundation for microservice fault diagnosis and mitigation, delivers practical guidance for industry practitioners, and pinpoints critical research directions for next-generation microservice engineering.

Microservice systems suffer from low fault localization accuracy and inefficient diagnosis due to strong inter-component interactions and independent deployment, severely undermining system reliability. To address this, we conduct a systematic literature review of 98 publications spanning 2003–2024. Our method integrates qualitative analysis, systematic review, and empirical investigation to construct a standardized diagnostic knowledge graph. We propose a novel multidimensional classification framework covering problem definitions, architectural paradigms, diagnostic dimensions, and evaluation criteria; unify publicly available datasets, toolchains, and metrics; and deliver a reusable technology selection guide. The study establishes the first comprehensive fault diagnosis landscape for microservices, clarifies current bottlenecks and evolutionary trajectories, and enables rapid industrial validation and deployment. Results demonstrate significant improvements in fault localization efficiency and overall system stability.

This study addresses the frequent misalignment between software modularity and organizational structure in microservice architectures, stemming from a lack of quantitative understanding of how developer activities relate to service boundaries. The work proposes the concept of “organizational cohesion,” extending the classic principle of “high cohesion, low coupling” to the organizational level, and introduces metrics such as Pairwise Team Cohesion (PTC) and Average Organizational Coupling (AOC). Through a longitudinal case study and multi-project replication, the research reveals systematic differences in organizational cohesion between core and peripheral services. Notably, PTC and AOC exhibit only weak correlation, indicating that team-level cohesion and cross-service development reflect distinct organizational dynamics. These findings empirically validate the decoupling between technical architecture and organizational structure in microservice systems.

This study addresses the fragmentation and lack of interoperability among existing microservice identification approaches by proposing the first unified framework based on a feature model. The framework systematically integrates diverse identification and refactoring methods through a systematic literature mapping, constructing a feature model that captures the primary variation points across current techniques. By analyzing concrete tool architectures instantiated within this model, the work reveals both the complementary nature of existing tools and the comprehensiveness of the overall design space. Results demonstrate that while individual tools cover only limited subsets of the variation points, the collective set of available tools nearly spans the entire spectrum defined by the feature model. This provides a solid theoretical foundation and practical guidance for future tool development and integration in microservice identification.

This work addresses the challenge of effectively evaluating the trade-offs between data consistency and coordination overhead among distributed transaction patterns—such as Saga and TCC—in business logic-intensive microservice systems prior to production deployment. The authors propose a lightweight microservice simulator grounded in Domain-Driven Design (DDD), which, for the first time, integrates DDD aggregate root modeling with multiple transaction models to decouple business logic from communication and transactional infrastructure. The framework supports configurable deployment topologies and network constraints, enabling seamless transitions from centralized to fully distributed architectures while providing a deterministic verification environment. Empirical evaluation on complex multi-aggregate systems quantifies the performance, coordination overhead, and resilience of different transaction models, substantially reducing development costs and facilitating left-shifted architectural validation.

This work addresses the challenges posed by microservice architectures—such as missing documentation, difficulty in understanding system structure, and architectural drift—stemming from decentralized, multi-repository development practices. Existing refactoring approaches struggle to generalize across projects due to their lack of modularity and technology-stack dependency. To overcome these limitations, we propose ModARO, a modular and technology-agnostic architecture reconstruction method that leverages reusable “extractors” to automatically analyze distributed codebases and reconstruct system architectures across projects. ModARO seamlessly integrates into CI/CD pipelines, enabling continuous architectural awareness. Empirical evaluation demonstrates its successful application to ten open-source systems, and a user study with eight industry practitioners confirms its significant superiority over existing baselines in terms of practicality and usability.

针对微服务架构中跨服务边界的代码克隆问题，开发了CC4M工具，通过检测和可视化手段辅助分析克隆代码的影响范围及维护成本。