Integrated model-driven development of self-adaptive user interfaces

Abstract

Modern user interfaces (UIs) are increasingly expected to be plastic, in the sense that they retain a constant level of usability, even when subjected to context changes at runtime. Self-adaptive user interfaces (SAUIs) have been promoted as a solution for context variability due to their ability to automatically adapt to the context-of-use at runtime. The development of SAUIs is a challenging and complex task as additional aspects like context management and UI adaptation have to be covered. In classical model-driven UI development approaches, these aspects are not fully integrated and hence introduce additional complexity as they represent crosscutting concerns. In this paper, we present an integrated model-driven development approach where a classical model-driven development of UIs is coupled with a model-driven development of context-of-use and UI adaptation rules. We base our approach on the core UI modeling language IFML and introduce new modeling languages for contextof-use (ContextML) and UI adaptation rules (AdaptML). The generated UI code, based on the IFML model, is coupled with the context and adaptation services, generated from the ContextML and AdaptML model, respectively. The integration of the generated artifacts, namely UI code, context, and adaptation services in an overall rule-based execution environment, enables runtime UI adaptation. The benefit of our approach is demonstrated by two case studies, showing the development of SAUIs for different application scenarios and a usability study which has been conducted to analyze end-user satisfaction of SAUIs.

CA-BPEL: A New Approach to Facilitate the Development and Execution of Context-Aware Service Orchestrations

“…Note that context information is not limited to the geographic location and includes various aspects such as weather situation (e.g., sunny, rainy, snowy or stormy), time of day (e.g., morning, noon, evening or midnight), available mobile networks (e.g., 2G, 3G, 4G or 5G), the user's device battery level (e.g., low, medium or high), the user's mood (e.g., normal, happy or sad), or the ambient light level (e.g., dim, normal or bright) (Salber et al, 1999;Hoyos et al, 2016;Moradi et al, 2020;Yigitbas et al, 2020).…”

“…Context-aware applications and processes exploit contextual data and information associated with the user and environment entities to automate user activities or make better decisions (Faieq et al, 2021). There exists a wide range of contextual information, e.g., the user's geographical and temporal situation, the user's mood, the user's device battery status, available mobile networks, and the weather status (Moradi et al, 2020;Yigitbas et al, 2020).…”

Model-based intelligent user interface adaptation: challenges and future directions

“…9c), which require the system to be decoupled from its intelligent UI. Current research efforts in the SE community [42] [3] are focused on providing strategies and facilities with which to support UI adaptation based on one control loop with an adaptation engine, and there is a shortage of approaches that support more intelligent strategies based on two control loops with an adaptation manager. Fig.…”

“…-Class level, when the process occurs at the level of the components belonging to specific software systems or provided by frameworks for this purpose. For example, Yigitbas et al [42] presented a model-driven approach for self-adaptive UIs that is applied at the model level of a particular UI. It supports the specification of an adaptation model that contains abstract UI adaptation rules in alignment with the IFML abstract UI modelling language.…”

“…compile), link or load time, dynamic, when its process takes place during runtime, or hybrid when both are combined. For example, in the Yigitbas et al approach [42] a rule-based execution environment supports the UI adaptation at runtime. 14 Adaptation time, which refers to the exact moment of time at which the UI adaptation occurs, which could be at one specific moment (single-step) or distributed throughout several moments of time (multi-step).…”