
Future computing systems must adjust to the user's situations, habits, and intentions. Self-adaptive applications autonomously adapt to changing contexts without asking the user. However, the self-adaptive behaviour lacks of success if it does not correspond to the user's personal interaction habits and intentions, particularly for complex scenarios with a high degree of user interaction. Concerning the interaction design, such adaptations can be irritating and distracting for the user if they do not match the current situation. In this article we provide a solution how to integrate the user in the self-adaptation feedback loop. The user will be able to influence the adaptation behaviour at run-time and in the long term by setting individual preferences. Consequently, we achieve a harmonisation between full application autonomy and user control. We implemented our generic concepts by extending an existing self-adaptation middleware with capabilities to respect the user's application focus and interaction behaviour. A notification-based solution for user participation has been evaluated in a substantial user study with 62 participants. Although participants perceived much better control with our solution, the study made clear that notification design is specific for each adaptation type.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 39 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
