Self-adaptation provides a principled way to deal with software systems’ uncertainty during operation. Examples of such uncertainties are disturbances in the environment, variations in sensor readings, and changes in user requirements. As more systems with strict goals require self-adaptation, the need for formal guarantees in self-adaptive systems is becoming a high-priority concern. Designing self-adaptive software using principles from control theory has been identified as one of the approaches to provide guarantees. In general, self-adaptation covers a wide range of approaches to maintain system requirements under uncertainty, ranging from dynamic adaptation of system parameters to runtime architectural reconfiguration. Existing control-theoretic approaches have mainly focused on handling requirements in the form of setpoint values or as quantities to be optimized. Furthermore, existing research primarily focuses on handling uncertainty in the execution environment. This article presents SimCA*, which provides two contributions to the state-of-the-art in control-theoretic adaptation: (i) it supports requirements that keep a value above and below a required threshold, in addition to setpoint and optimization requirements; and (ii) it deals with uncertainty in system parameters, component interactions, system requirements, in addition to uncertainty in the environment. SimCA* provides guarantees for the three types of requirements of the system that is subject to different types of uncertainties. We evaluate SimCA* for two systems with strict requirements from different domains: an Unmanned Underwater Vehicle system used for oceanic surveillance and an Internet of Things application for monitoring a geographical area. The test results confirm that SimCA* can satisfy the three types of requirements in the presence of different types of uncertainty.

中文翻译：

---

SimCA*

自适应为处理软件系统在运行过程中的不确定性提供了一种原则性的方法。这种不确定性的例子是环境中的干扰、传感器读数的变化以及用户需求的变化。随着越来越多的具有严格目标的系统需要自适应，自适应系统中对形式保证的需求正成为一个高优先级的问题。使用控制理论的原理设计自适应软件已被确定为提供保证的方法之一。一般来说，自适应涵盖了在不确定性下维持系统要求的广泛方法，从系统参数的动态适应到运行时架构重新配置。现有的控制理论方法主要集中在以设定值或要优化的量的形式处理要求。此外，现有研究主要集中在处理执行环境中的不确定性。本文介绍了 SimCA*，它为控制理论自适应的最新技术提供了两个贡献：(i) 除了设定点和优化要求外，它还支持将值保持在所需阈值之上和之下的要求；(ii) 除了环境中的不确定性之外，它还处理系统参数、组件相互作用、系统要求的不确定性。SimCA* 为受不同类型不确定性影响的系统的三类要求提供保证。我们针对两个具有不同领域严格要求的系统评估 SimCA*：用于海洋监视的无人水下航行器系统和用于监测地理区域的物联网应用程序。测试结果证实，在存在不同类型不确定性的情况下，SimCA* 可以满足三类要求。