Software systems are increasingly required to autonomously adapt their architectural structures and/or behaviors to runtime environmental changes. However, existing architecture-based self-adaptation approaches mostly focus on structural adaptations within a predefined space of architectural alternatives (e.g., switching between two alternative services) while merely considering quality constraints (e.g., reliability and performance). In this paper, we propose a new architecture-based self-adaptation approach, which performs behavioral adaptations with automatically generated alternatives and supports relaxed functional constraints from the perspective of business value. Specifically, we propose a technique to automatically generate behavioral alternatives of a software system from the currently-employed architectural behavioral specification. We employ business value to comprehensively evaluate the behavioral alternatives while capturing the trade-offs among relaxed functional and quality constraints. We also introduce a genetic algorithm-based planning technique to efficiently search for the optimal (sometimes a near-optimal) behavioral alternative that can provide the best business value. The experimental study on an online order processing benchmark has shown promising results that the proposed approach can improve adaptation flexibility and business value with acceptable performance overhead.

Users increasingly depend on mobile applications to get access to software services, social networks, and physical devices. When using mobile applications, users often want to achieve personal goals rather than merely perform individual tasks. To achieve a goal, a user often needs to combine software services, social cooperation, and possibly manual work. Moreover, a goal can often be achieved in different ways, each of which involves an alternative sequence of tasks. Accordingly, mobile applications should be customizable, to accommodate user preferences, and adaptive in changing their configuration automatically if the current configuration is failing. In this paper, we propose an improved runtime goal model that can manage runtime lifecycle of goals and adaptively schedule the activation of goals and execution of tasks. Based on the model, we propose an agent-based framework called MobiGoal, which combines software services, social cooperation, and manual work for achieving user goals and provides an infrastructure for developing customizable and adaptive mobile applications for personal goals. We have developed an implementation for Android platform and conducted an empirical study. The results show that MobiGoal applications can effectively support users to adaptively achieve their goals and MobiGoal can significantly save effort of application development for specific goals.

Collaborative work supported by mobile applications has become more and more popular. Mobile collaboration in some cases needs to be conducted in an interactive way to allow the sharing of the requester screen with the collaborator. Existing interactive screen sharing techniques, however, may cause heavy network traffic and high latency and lack fine-grained control of the scope of collaboration. In this paper, we propose CollaDroid, a lightweight and UI Description based technique for interactive collaboration of Android applications. CollaDroid can automatically transform an Android application to a collaboration augmented application with which a requester can interactively collaborate with a remote collaborator by synchronizing UI (User Interface) content and events. The results of our experimental study show that CollaDroid is applicable for a large part of applications in the Android Market and can provide an efficient collaboration mechanism with low network traffic and latency. And the results of our user study show that the collaboration mechanism implemented by CollaDroid is well accepted by users.