[论文解读] ActivFORMS: A Model-Based Approach to Engineer Self-Adaptive Systems

Danny Weyns, M. Usman Iftikhar|arXiv (Cornell University)|Aug 29, 2019

Advanced Software Engineering Methodologies参考文献 70被引用 17

一句话总结

ActivFORMS 是一种基于模型的方法，通过形式化验证的模型确保自适应系统中反馈回路的正确运行时行为，使用统计模型检测高效选择适应选项，并支持运行时更新适应目标和模型。它在列日的基于物联网的建筑安防监控系统中得到验证，实现了在不确定环境下的可靠、高效和动态自适应。

ABSTRACT

Handling change is an increasingly important challenge for software engineers. Our focus is on changes caused by uncertainties in the operating conditions of a system, such as changes in the availability of resources in a highly dynamic environment. To deal with such uncertainties, an external feedback loop system can be added to the system that collects additional data during operation to resolve the uncertainties and adapt the system to achieve particular quality requirements (i.e., adaptation goals); this approach is commonly referred to as self-adaptation. To ensure that the system complies with the adaptation goals, recent research suggests the use of formal techniques at runtime. Existing approaches have three shortcomings that limit their practical applicability: (i) they ignore correctness of the behavior of the feedback loop, (ii) they apply exhaustive verification at runtime to select adaptation options to realize the adaptation goals, which is very resource demanding, and (iii) they provide limited or no support for changing adaptation goals at runtime. To tackle these shortcomings, we present ActivFORMS (Active FORmal Models for Self-adaptation). ActivFORMS: (i) provides guarantees for the correct behavior of the feedback loop with respect to a set of correctness properties at design time and preserves the guarantees at runtime by directly executing the verified models of the feedback loop, (ii) guides the adaptation of the system by selecting adaptation options that realize the adaptation goals in an efficient manner using statistical model checking at runtime, and (iii) offers basic support for changing adaptation goals and updating verified models of the feedback loop on-the-fly to meet the new goals. To validate ActivFORMS, we present a tool-supported instance of the approach that we apply to an IoT application for building security monitoring deployed in Leuven.

研究动机与目标

• 解决现有自适应方法在反馈回路正确性保证、运行时验证成本高以及对运行时目标变更支持不足等方面的局限性。
• 通过设计时的形式化验证和运行时执行已验证模型，确保反馈回路行为的正确性。
• 通过用统计模型检测替代全面验证，降低适应的计算成本，以高效选择适应选项。
• 支持在运行时对适应目标和已验证反馈回路模型进行动态更新，以适应不断变化的系统需求。
• 在列日的现实世界物联网部署中对建筑安防监控系统进行验证。

提出的方法

• 使用形式化技术在设计时指定并验证反馈回路的形式化模型，以保证正确性属性。
• 在运行时直接执行已验证模型，以确保反馈回路的行为正确性。
• 在运行时应用统计模型检测，以高效评估并选择满足适应目标的适应选项。
• 该方法支持对适应目标和已验证反馈回路模型进行运行时修改，以及增量更新以反映新目标。
• 实现并评估了一个工具支持的 ActivFORMS 实例，应用于列日的基于物联网的建筑安防监控系统。

实验结果

研究问题

• RQ1 如何在设计时和运行时都保证自适应系统中反馈回路行为的正确性？
• RQ2 统计模型检测能否替代全面验证，以降低运行时适应成本，同时确保适应目标的合规性？
• RQ3 在不损害正确性的情况下，适应目标和反馈回路模型在运行时可动态更新的程度有多大？
• RQ4 ActivFORMS 在现实世界物联网部署中实现高效且正确的自适应效果如何？

主要发现

• ActivFORMS 通过设计时的形式化验证和运行时执行已验证模型，确保了反馈回路行为的正确性。
• 统计模型检测实现了适应选项的高效选择，与全面验证相比显著降低了计算开销。
• 该方法支持对适应目标和已验证反馈回路模型进行运行时更新，实现了对不断变化需求的动态适应。
• ActivFORMS 的工具支持实现成功应用于列日的基于物联网的建筑安防监控系统，证明了其实际适用性。