架构退化：如何度量与修复
Architectural Degradation: How to Measure and to Remediate
- University of Oulu（奥卢大学）
- University Southern Denmark（南丹麦大学）
- Free University of Bozen-Bolzano（博尔扎诺自由大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究通过多语种文献综述，系统梳理了架构退化的度量方法、指标、工具与修复策略，发现诊断工具成熟但修复整合不足，并指出诊断-修复差距是未来研究关键方向。
AI中文摘要：
背景。架构退化会损害软件的可维护性、可演化性和质量。然而，现有研究在度量方法、度量指标、工具和修复策略方面仍然分散，限制了我们对这些要素在整个退化生命周期中如何关联的理解。目标。我们通过考察研究者如何度量架构退化、哪些指标和工具支持其评估，以及现有方法如何处理修复，来整合架构退化领域的研究现状。方法。我们进行了一项多语种文献综述，涵盖284项同行评审和灰色文献研究。我们使用本地执行的、结合检索增强生成、多模型验证和人工裁决的LLM辅助流水线来支持筛选、数据提取和分类。随后，我们分析了所得分类法及其跨维度关系。结果与结论。我们识别出277种度量方法、357个度量指标、238个工具和395种修复方法。研究高度集中于静态和结构分析、结构指标以及面向检测的工具。相比之下，修复涵盖异构的代码级、架构级和组织级干预措施，且整合程度明显较低。总体而言，该领域已发展出成熟的诊断工具，但在将退化检测与有效修复相连接方面进展较少。我们的结果为现有技术提供了结构化视图，并指出诊断-修复差距是未来研究的关键方向。
英文摘要：
Context. Architectural degradation undermines software maintainability, evolvability, and quality. However, existing research remains fragmented across measurement approaches, metrics, tools, and remediation strategies, limiting our understanding of how these elements relate across the degradation lifecycle. Aim. We consolidate the state of the art on architectural degradation by examining how researchers measure it, which metrics and tools support its assessment, and how existing approaches address remediation. Method. We conducted a Multivocal Literature Review of 284 peer-reviewed and grey-literature studies. We supported screening, data extraction, and classification with a locally executed LLM-assisted pipeline combining Retrieval-Augmented Generation, multi-model validation, and human adjudication. We then analyzed the resulting taxonomies and their cross-dimensional relationships. Results and Conclusions. We identified 277 measurement approaches, 357 metrics, 238 tools, and 395 remediation approaches. Research strongly concentrates on static and structural analysis, structural metrics, and detection-oriented tools. In contrast, remediation spans heterogeneous code-level, architectural, and organizational interventions and shows substantially less consolidation. Overall, the field has developed a mature diagnostic apparatus but has made less progress in connecting degradation detection with effective remediation. Our results provide a structured view of the available techniques and identify the diagnosis-remediation gap as a key direction for future research.
