Facial Affect Analysis (FAA) is evolving from a stand-alone recognition task into a reusable perception capability for Service-Oriented Software Ecosystems (SoSE). This paper preserves the FAA methodological core while reframing recent advances through systems-engineering requirements for composable and dependable services. We review representative progress in static and dynamic expression analysis, action-unit and micro-expression modeling, and modern CNN, Transformer, graph, and hybrid architectures, then interpret these advances by their operational fit in edge, cloud, and hybrid service pipelines. The synthesis emphasizes SoSE concerns that determine deployability: service contracts for uncertainty-aware outputs, latency and availability envelopes, lifecycle monitoring and recalibration, governance-aware integration, and interoperability across independently evolving components. Our analysis shows that benchmark gains alone are insufficient for SoSE readiness; robustness under shift, intervention stability, fairness, privacy posture, and runtime guarantees are equally critical. We conclude with a roadmap for treating FAA as an operational service component with explicit interfaces, measurable quality attributes, and accountable lifecycle management.

翻译：面部情感分析（Facial Affect Analysis，FAA）正从一项独立的识别任务演变为面向服务型软件生态系统（Service-Oriented Software Ecosystems，SoSE）的可复用感知能力。本文在保留FAA方法论核心的基础上，通过可组合与可信赖服务的系统工程需求，重新诠释了该领域的最新进展。我们回顾了静态与动态表情分析、动作单元与微表情建模，以及现代CNN、Transformer、图神经网络与混合架构中的代表性成果，并依据这些方法在边缘、云端及混合服务流水线中的操作适配性进行解读。本文综合强调了决定部署可行性的SoSE关注点：面向不确定性感知输出的服务契约、延迟与可用性边界、生命周期监控与重校准、治理感知集成，以及跨独立演化组件的互操作性。我们的分析表明，仅凭基准性能提升不足以满足SoSE就绪性要求；漂移鲁棒性、干预稳定性、公平性、隐私保护状态及运行时保障同样至关重要。最后，我们提出了一份将FAA视为具有显式接口、可量化质量属性及可问责生命周期管理的操作性服务组件的路线图。