Modern software applications are subject to uncertain operating conditions, such as dynamics in the availability of services and variations of system goals. Consequently, runtime changes cannot be ignored, but often cannot be predicted at design time. Control theory has been identified as a principled way of addressing runtime changes and it has been applied successfully to modify the structure and behavior of software applications. Most of the times, however, the adaptation targeted the resources that the software has available for execution (CPU, storage, etc.) more than the software application itself. This paper investigates the research efforts that have been conducted to make software adaptable by modifying the software rather than the resource allocated to its execution. This paper aims to identify: the focus of research on control-theoretical software adaptation; how software is modeled and what control mechanisms are used to adapt software; what software qualities and controller guarantees are considered. To that end, we performed a systematic literature review in which we extracted data from 42 primary studies selected from 1512 papers that resulted from an automatic search. The results of our investigation show that even though the behavior of software is considered non-linear, research efforts use linear models to represent it, with some success. Also, the control strategies that are most often considered are classic control, mostly in the form of Proportional and Integral controllers, and Model Predictive Control. The paper also discusses sensing and actuating strategies that are prominent for software adaptation and the (often neglected) proof of formal properties. Finally, we distill open challenges for control-theoretical software adaptation.

Today customers require software systems to provide particular levels of qualities, while operating under dynamically changing conditions. These requirements can be met with different self-adaptation approaches. Recently, we developed two approaches that are different in nature - control theory-based SimCA and architecture-based ActivFORMS - to endow software systems with self-adaptation, providing guarantees on desired behavior. However, it is unclear which of the two approaches should be used in different adaptation scenarios and how effective they are in comparison to each other. In this paper, we apply SimCA and ActivFORMS to the Tele Assistance System (TAS) exemplar and compare obtained results, demonstrating the difference in achieved qualities and formal guarantees.

An increasingly important concern of software engineers is handling uncertainties at design time, such as environment dynamics that may be difficult to predict or requirements that may change during operation. The idea of self-adaptation is to handle such uncertainties at runtime, when the knowledge becomes available. As more systems with strict requirements require self-adaptation, providing guarantees for adaptation has become a high-priority. Providing such guarantees with traditional architecture-based approaches has shown to be challenging. In response, researchers have studied the application of control theory to realize self-adaptation. However, existing control-theoretic approaches applied to adapt software systems have primarily focused on satisfying only a single adaptation goal at a time, which is often too restrictive for real applications. In this paper, we present Simplex Control Adaptation, SimCA, a new approach to self-adaptation that satisfies multiple goals, while being optimal with respect to an additional goal. SimCA offers robustness to measurement inaccuracy and environmental disturbances, and provides guarantees. We evaluate SimCA for two systems with strict requirements that have to deal with uncertainties: an underwater vehicle system used for oceanic surveillance, and a tele-assistance system for health care support.

Self-adaptation provides a principled way to deal with change during operation. As more systems with strict goals require self-adaptation, the need for guarantees in self-adaptive systems is becoming a high-priority concern. Designing adaptive software using principles from control theory has been identified as one of the approaches to provide guarantees. However, current solutions can only handle pre-specified requirements either in the form of setpoint values (S-reqs) or values to be optimized (O-reqs). This paper presents SimCA* that makes two contributions to control-based self-adaptation: (a) it allows the user to specify a third type of requirement that keeps a value above/below a threshold (T-reqs); and (b) it can deal with requirement sets that change at runtime (i.e., requirements can be adjusted, activated, and deactivated on the fly). SimCA* offers robustness to disturbances and provides adaptation guarantees. We evaluate SimCA* for two systems with strict goals from different domains: an underwater vehicle system used for oceanic surveillance, and a tele-assistance system for health care support. The test results demonstrate that SimCA* can deal with the three types of requirements (STO-reqs) operating under various types of dynamics and the set of requirements can be changed on the fly.