Context: Modern Systems of Systems (SoSs) increasingly operate in dynamic environments (e.g., smart cities, autonomous vehicles) where runtime composition -- the on-the-fly discovery, integration, and coordination of constituent systems (CSs)--is crucial for adaptability. Despite growing interest, the literature lacks a cohesive synthesis of runtime composition in dynamic SoSs. Objective: This study synthesizes research on runtime composition in dynamic SoSs and identifies core challenges, solution strategies, supporting tools, and evaluation methods. Methods: We conducted a Systematic Literature Review (SLR), screening 1,774 studies published between 2019 and 2024 and selecting 80 primary studies for thematic analysis (TA). Results: Challenges fall into four categories: modeling and analysis, resilient operations, system orchestration, and heterogeneity of CSs. Solutions span seven areas: co-simulation and digital twins, semantic ontologies, integration frameworks, adaptive architectures, middleware, formal methods, and AI-driven resilience. Service-oriented frameworks for composition and integration dominate tooling, while simulation platforms support evaluation. Interoperability across tools, limited cross-toolchain workflows, and the absence of standardized benchmarks remain key gaps. Evaluation approaches include simulation-based, implementation-driven, and human-centered studies, which have been applied in domains such as smart cities, healthcare, defense, and industrial automation. Conclusions: The synthesis reveals tensions, including autonomy versus coordination, the modeling-reality gap, and socio-technical integration. It calls for standardized evaluation metrics, scalable decentralized architectures, and cross-domain frameworks. The analysis aims to guide researchers and practitioners in developing and implementing dynamically composable SoSs.

翻译：背景：现代系统之系统（SoSs）日益在动态环境（例如智慧城市、自动驾驶车辆）中运行，其中运行时组合——即对组成系统（CSs）的即时发现、集成与协调——对于适应性至关重要。尽管关注度日益增长，现有文献仍缺乏对动态SoS中运行时组合的连贯性综合。目标：本研究综合了动态SoS中运行时组合的相关研究，并识别了核心挑战、解决策略、支持工具及评估方法。方法：我们进行了系统性文献综述（SLR），筛选了2019年至2024年间发表的1,774项研究，并选取了80项主要研究进行主题分析（TA）。结果：挑战可分为四类：建模与分析、弹性运行、系统编排以及CSs的异构性。解决方案涵盖七个领域：协同仿真与数字孪生、语义本体、集成框架、自适应架构、中间件、形式化方法以及AI驱动的弹性。面向服务的组合与集成框架在工具中占主导地位，而仿真平台则支持评估。工具间的互操作性、有限的跨工具链工作流以及标准化基准的缺失仍是主要差距。评估方法包括基于仿真的研究、实现驱动的研究以及以人为中心的研究，这些方法已在智慧城市、医疗保健、国防和工业自动化等领域得到应用。结论：本综合揭示了若干张力，包括自主性与协调性之间的权衡、建模与现实的差距以及社会技术集成问题。研究呼吁建立标准化的评估指标、可扩展的去中心化架构以及跨领域框架。该分析旨在指导研究人员和实践者开发与实施动态可组合的SoS。