AI 中文总结
研究针对决策地图在自适应系统安全建模上的不足，通过引入新维度和采用分治方法扩展建模符号，经实际用例验证，该扩展能更准确捕捉安全场景，为自适应生命周期提供全面支持。
AI 中文摘要
可持续性指系统维持功能并长期存续的能力，是软件系统（包括自适应系统，SAS）的理想属性。SAS可在运行时改变行为以达成目标，但决策地图（DMs）虽有帮助，却缺乏对安全问题的充分建模支持。为此，扩展SAS的可持续性驱动建模符号，引入安全事件建模维度，采用细粒度分治方法从不同时间安全视角建模。通过行业伙伴提供的实际用例评估其可行性与适用性，结果表明该建模符号能更准确捕捉安全场景，为自适应生命周期阶段提供全面支持。
英文摘要
Sustainability refers to a system's ability to maintain its functionality and endure over time. Hence, sustainability is a highly desirable property of software systems, including Self-Adaptive Systems (SASs). SASs can change (adapt) their behavior at runtime to continue achieving their objectives despite external or internal impacts. SASs' intended long-term system behavior can be expressed through a sustainability-driven visual modeling notation called Decision Maps (DMs). Although DMs have been proven helpful, they lack adequate modeling support for safety and security concerns. We address this limitation by extending the current notation for sustainability-driven modeling of SASs to better accommodate the unique characteristics of safety and security scenarios. First, we introduce an additional modeling dimension to account for safety incidents. Second, we adopt a fine-grained divide-and-conquer approach, modeling from distinct temporal security viewpoints ("security modes") to address security. We employ the extended DM notation in a real-world use case scenario provided by our industry partner to assess its feasibility and suitability for practitioners. Our results indicate that our modeling notation helps capture security and safety scenarios more accurately and provides holistic support for the self-adaptation life cycle phases.
