Generic controllers for self-adaptive systems can be configured parametrically according to system needs, even though their reuse is restricted because of the wide range of services that may be provided by each stage of a feedback control loop, like MAPE-K. Rainbow is a typical example of such a generic, monolithic controller. This article revisits and extends prior work that advocates structurally flexible controllers, as ensembles of micro-controllers each providing specific services. We experimented with our approach with three different architectural configurations for the controller—monolithic, decentralised and decentralised with a meta-controller. Our results indicate that despite the decentralised configuration with a meta-controller demanding more computational resources, it performed comparatively well compared to the other configurations, including when measuring the target system’s response time. Moreover, we found that variations of the control loop timing at the different layers of the controller impact the stability of the target system. We have also evolved the controller by adding a new micro-controller, which caused no impact on the other micro-controllers, and mostly kept the target system’s performance. We conclude that a multi-layered controller design, based on micro-controllers, provides the basis for defining structurally flexible controllers at operational-time and may promote reuse at development-time.

In self-adaptive software systems, generic controllers can be configured parametrically according to system needs, even though their reuse is restricted because of the wide range of services that can be provided by each of the stages of a feedback control loop, like MAPE-K. Rainbow is a typical example of such a generic, monolithic controller. This paper advocates controllers that are structurally flexible, and which are composed from micro-controllers, each providing specific services (e.g., based on microservices). To provide evidence on the feasibility of our approach, we compare three different architectural configurations for the controller: monolithic, decentralised, and decentralised with a meta-controller. Results from our experiments indicate that even though the decentralised configuration with a meta-controller demanded more computational resources, it performed comparatively well when compared to the other configurations. We conclude that a multi-layered controller design, based on micro-controllers, provides the basis for defining structurally flexible controllers at operational-time, and may promote reuse at development-time.

Summary Adaptive systems (ASs) and context‐aware systems (CASs) are able to evaluate their own behaviour and toadaptit when the system fails to accomplish its goals or when better functionality or performance is possible. Ensuring the reliability of ASs and CASs is demanding because failures might have undesirable consequences. Testing ASs and CASs effectively is not trivial because of the inherent characteristics of these systems. The literature lacks a comprehensive review that provides a broad picture of the area; current reviews are outdated and incomplete. The objectives of this study are characterizing the state of the art in AS and CAS testing and discussing approaches, challenges, observed trends, and research limitations and directions. We performed a systematic literature review (SLR) and a thematic analysis of studies, reporting up‐to‐date, refined and extended results when compared with existing reviews. Based on 102 selected studies, we (i) characterized testing approaches by grouping techniques for ASs and CASs; (ii) updated and refined a characterization of testing challenges for ASs and CASs; and (iii) analysed and discussed research trends and implications for AS and CAS testing. There are recurring research concerns regarding AS and CAS testing. Examples are the generation of test cases and built‐in tests. Moreover, we also identified recurring testing challenges such as context monitoring and runtime decisions. Moreover, there are some trends such as model‐based testing and hybrid techniques and some little investigated issues like uncertainty and prediction of changes. All in all, our results may provide guidance for developers and researchers with respect to the practice and the future research on AS and CAS testing.

An adaptive system (AS) evaluates its own behavior and changes it when the evaluation indicates that the system is not accomplishing what it is intended to do, or when better functionality or performance is possible. MAPE-K is a reference model that prescribes the adaptation mechanism of ASs by means of high-level abstractions such as Monitors, Analyzers, Planners and Executors and the relationships among them. Since the abstractions and the relationships provided by MAPE-K are generic, other reference models were proposed focusing on providing lower level abstractions to support software engineers in a more suitable way. However, after the analysis of seven representative ASs, we realized the abstractions prescribed by the existing reference models are not properly implemented, thus leading to architectural drifts. Therefore, in this paper we characterized three of these drifts by describing them with a template and showing practical examples. The three architectural drifts of ASs are Scattered Reference Inputs, Mixed Executors and Effectors, and Obscure Alternatives. We expect that by identifying and characterizing these drifts, we can help software architects improve their design and, as a consequence, increase the reliability of this type of systems.