336 research outputs found

    Adaptive model-driven user interface development systems

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    Adaptive user interfaces (UIs) were introduced to address some of the usability problems that plague many software applications. Model-driven engineering formed the basis for most of the systems targeting the development of such UIs. An overview of these systems is presented and a set of criteria is established to evaluate the strengths and shortcomings of the state-of-the-art, which is categorized under architectures, techniques, and tools. A summary of the evaluation is presented in tables that visually illustrate the fulfillment of each criterion by each system. The evaluation identified several gaps in the existing art and highlighted the areas of promising improvement

    Preserving designer input on concrete user interfaces using constraints while maintaining adaptive behavior

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    User interface (UI) adaptation is applied when a single UI design might not be adequate for maintaining usability in multiple contexts-of-use that can vary according to the user, platform, and environment. Fully-automated UI generation techniques have been criticized for not matching the ingenuity of human designers and manual UI adaptation has also been criticized for being time consuming especially when it is necessary to adapt the UI for a large number of contexts. This paper presents a work-in-progress approach that uses constraints for preserving designer input on concrete user interfaces upon applying adaptive behavior. The constraints can be assigned by the UI designer using our integrated development environment Cedar Studio

    Engineering Adaptive Model-Driven User Interfaces

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    Software applications that are very large-scale, can encompass hundreds of complex user interfaces (UIs). Such applications are commonly sold as feature-bloated off-the-shelf products to be used by people with variable needs in the required features and layout preferences. Although many UI adaptation approaches were proposed, several gaps and limitations including: extensibility and integration in legacy systems, still need to be addressed in the state-of-the-art adaptive UI development systems. This paper presents Role-Based UI Simplification (RBUIS) as a mechanism for increasing usability through adaptive behaviour by providing end-users with a minimal feature-set and an optimal layout, based on the context-of- use. RBUIS uses an interpreted runtime model-driven approach based on the Cedar Architecture, and is supported by the integrated development environment (IDE), Cedar Studio. RBUIS was evaluated by integrating it into OFBiz, an open-source ERP system. The integration method was assessed and measured by establishing and applying technical metrics. Afterwards, a usability study was carried out to evaluate whether UIs simplified with RBUIS show an improvement over their initial counterparts. This study leveraged questionnaires, checking task completion times and output quality, and eye-tracking. The results showed that UIs simplified with RBUIS significantly improve end-user efficiency, effectiveness, and perceived usability

    Integrating adaptive user interface capabilities in enterprise applications

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    Many existing enterprise applications are at a mature stage in their development and are unable to easily benefit from the usability gains offered by adaptive user interfaces (UIs). Therefore, a method is needed for integrating adaptive UI capabilities into these systems without incurring a high cost or significantly disrupting the way they function. This paper presents a method for integrating adaptive UI behavior in enterprise applications based on CEDAR, a model-driven, service-oriented, and tool-supported architecture for devising adaptive enterprise application UIs. The proposed integration method is evaluated with a case study, which includes establishing and applying technical metrics to measure several of the method’s properties using the open-source enterprise application OFBiz as a test-case. The generality and flexibility of the integration method are also evaluated based on an interview and discussions with practitioners about their real-life projects

    Task-based Adaptation of Graphical Content in Smart Visual Interfaces

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    To be effective visual representations must be adapted to their respective context of use, especially in so-called Smart Visual Interfaces striving to present specifically those information required for the task at hand. This thesis proposes a generic approach that facilitate the automatic generation of task-specific visual representations from suitable task descriptions. It is discussed how the approach is applied to four principal content types raster images, 2D vector and 3D graphics as well as data visualizations, and how existing display techniques can be integrated into the approach.Effektive visuelle Repräsentationen müssen an den jeweiligen Nutzungskontext angepasst sein, insbesondere in sog. Smart Visual Interfaces, welche anstreben, möglichst genau für die aktuelle Aufgabe benötigte Informationen anzubieten. Diese Arbeit entwirft einen generischen Ansatz zur automatischen Erzeugung aufgabenspezifischer Darstellungen anhand geeigneter Aufgabenbeschreibungen. Es wird gezeigt, wie dieser Ansatz auf vier grundlegende Inhaltstypen Rasterbilder, 2D-Vektor- und 3D-Grafik sowie Datenvisualisierungen anwendbar ist, und wie existierende Darstellungstechniken integrierbar sind

    Designing and Implementing a Framework for Real-time Robot Controller Clients

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    This research paper designs a framework for developing real-time clients that communicate with robot controllers built by students at the University of Stavanger. The framework provides patterns that handle time-sensitive components and demonstrates a technique for functional scalability. A brief section introduces design metrics for user experience. The report presents three use cases covering functionality for actuating a robot and reading its movements in real time. This thesis implemented the three use cases in the spring semester of 2022, and the results show that it is possible to model use cases, but implementing complex use cases requires more effort
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