Learn More
In earlier work we proposed the idea of requirements-aware systems that could introspect about the extent to which their goals were being satisfied at runtime. When combined with requirements monitoring and self adaptive capabilities, requirements awareness should help optimize goal satisfaction even in the presence of changing run-time context. In this(More)
—Autonomous systems are increasingly conceived as a means to allow operation in changeable or poorly understood environments. However, granting a system autonomy over its operation removes the ability of the developer to be completely sure of the system's behaviour under all operating contexts. This combination of environmental and behavioural uncertainty(More)
[Context and motivation] All systems are susceptible to the need for change, with the desire to operate in changeable environments driving the need for software adaptation. A Dynamically Adaptive System (DAS) adjusts its behaviour autonomously at runtime in order to accommodate changes in its operating environment, which are anticipated in the system's(More)
Dynamically adaptive systems (DASs) change behaviour at run-time to operate in volatile environments. As we learn how best to design and build systems with greater autonomy, we must also consider when to do so. Thus far, DASs have tended to showcase the benefits of adaptation infrastructures with little understanding of what characterizes the problem(More)
—The behaviour of self adaptive systems can be emergent. The difficulty in predicting the system's behaviour means that there is scope for the system to surprise its customers and its developers. Because its behaviour is emergent, a self-adaptive system needs to garner confidence in its customers and it needs to resolve any surprise on the part of the(More)
—A self-adaptive system adjusts its configuration to tolerate changes in its operating environment. To date, requirements modeling methodologies for self-adaptive systems have necessitated analysis of all potential system configurations, and the circumstances under which each is to be adopted. We argue that, by explicitly capturing and modelling uncertainty(More)