CI/CD pipelines are central to DevOps practices, yet their growing complexity makes them increasingly difficult to interpret, analyze, and systematically evolve. Existing tooling primarily offers execution logs and static graph representations, providing limited support for structured analysis of pipeline behavior, failures, and version-to-version evolution. This paper presents a model-driven Digital Twin (DT) for CI/CD pipelines that leverages BPMN as a model-ing backbone to transform raw CI configurations into structured, higher-level process representations. The proposed DT architecture enables visual abstraction of pipeline structure, failure tracing, and systematic version comparison, supporting both monitoring and evolution analysis of DevOps processes. Building upon validated DT architectural principles and prior work on build optimization and anomaly detection, the framework provides a modular, extensible foundation for integrating advanced analytical and prescriptive services into software delivery processes. The approach is validated using open-source CI/CD projects, and ongoing work targets the integration of additional improvement services and the extension of the DT to broader DevOps lifecycle processes.

翻译：持续集成/持续交付（CI/CD）流水线是DevOps实践的核心，但其日益增长的复杂性使得解释、分析和系统性演化的难度显著增加。现有工具主要提供执行日志和静态图形表示，对流水线行为、故障及版本间演化的结构化分析支持有限。本文提出一种面向CI/CD流水线的模型驱动数字孪生（Digital Twin, DT）方法，该方法以BPMN为建模主干，将原始CI配置转化为结构化的高层过程表示。所提出的DT架构能够实现流水线结构的可视化抽象、故障追踪及系统性版本对比，同时支持DevOps流程的监控与演化分析。该框架建立在已验证的DT架构原则及前期关于构建优化与异常检测的研究基础之上，为将高级分析与处方服务集成到软件交付流程中提供了模块化、可扩展的基础。通过开源CI/CD项目对方法进行了验证，当前工作旨在集成更多改进服务，并将DT扩展至更广泛的DevOps生命周期流程。