Self-explanatory user interfaces by model-driven engineering

Frey, Alfonso García

doi:10.1145/1822018.1822076

Cited by 6 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several approaches were proposed for developing UI help using different techniques including: crowdsourcing [9], model‐driven engineering [10], pixel analysis [11], and so on. Some of the proposed approaches focus on the generation of UI help.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Generating contextual help for user interfaces from software requirements

Akiki

2019

IET softw.

View full text Add to dashboard Cite

Software requirements are an essential stepping stone for engineering any software system that meets the needs of its stakeholders. User interface (UI) contextual help provides end users with much-needed support for understanding how to use a software system. This article presents an approach for generating contextual help from software requirements, while maintaining the ability to provide human input on the generated help. Domain classes, use cases, and UI flow models embody information that is valuable for help generation and are thereby used by the proposed approach. Templates are also used to define how requirements are associated with their contextual help counterpart elements. The generated help is represented using an existing contextual help definition language called CHAINXML. The latter was extended to support templates and alternatives in order to make the help generation process more seamless and to reduce the repetition in the generated help. The usefulness (usability and utility) of the generated help was evaluated by conducting a study with end users. The results showed that the participants found the help to be highly useful and most of them chose to use this help when given the opportunity to do so in a real-life case.

show abstract

Section: Related Workmentioning

confidence: 99%

“…García Frey et al generate self‐explanatory UIs based on task models [10]. Some approaches keep their design‐time models alive at runtime to support dynamic operations.…”

Section: Related Workmentioning

confidence: 99%

Generating contextual help for user interfaces from software requirements

Akiki

2019

IET softw.

View full text Add to dashboard Cite

show abstract

“…Some of these tools such as UsiComp [García Frey et al 2012] and Xplain [García Frey et al 2010] are early-stage research prototypes that provide a limited number of features. The UI models representing the different levels of abstraction are designed in UsiComp inside a single document-style panel.…”

Section: Cedar Studiomentioning

confidence: 99%

Adaptive Model-Driven User Interface Development Systems

2014

View full text Add to dashboard Cite

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. The user interface (UI) layer is considered one of the key components of software applications since it connects their end-users to the functionality. Well-engineered and robust software applications could eventually fail to be adopted due to a weak UI layer. Some user interface development techniques such as: universal design [Mace et al. 1990], inclusive design [Keates et al. 2000], and design for all [Stephanidis 1997] promote the concept of making one UI design fit as many people as possible. Yet, a UI is not independent from its context-of-use, which is defined in terms of the user, platform, and environment [Calvary et al. 2003]. The "one design fits all" approach is unable to accommodate all the cases of variability in the context-of-use, in many cases leading to a diminished user experience. Building multiple UIs for the same functionality due to context variability is difficult since the scope of variability cannot be completely known at design-time and there is a high cost incurred by manually developing multiple versions of the UI. Adaptive UIs have been promoted as a solution for context variability due to their ability to automatically adapt to the context-of-use at runtime. User interfaces capable of adapting to their context-of-use are also referred to as multi-context or multi-target [Fonseca 2010]. A key goal behind adaptive UIs is plasticity denoting a UI's ability to preserve its usability across multiple contexts-of-use [Coutaz 2010]. Norcio and Stanley [1989] consider that the idea of an adaptive UI is straightforward since it simply means that: "The interface should adapt to the user; rather than the user adapting to the system" (p. 399) but they note that in spite of the simplicity of the definition, there are some difficult and complex problems relating to adaptive UIs. In our study of the literature, we noticed that some of these problems are technical and are related to devising systems that can support the development of adaptive UIs, while others are related to human factors such as the end-user acceptance of these UIs. Realizing the abstract properties illustrated in Fig. 1, could help in handling some of the technical and human problems related to adaptive UIs. Salehie and Tahvildari [2009] present a hierarchy of adaptability properties for software systems, referred to as self-* properties. This hierarchy demon...

show abstract

Systematic literature review of the objectives, techniques, kinds, and architectures of models at runtime

Szvetits

Zdun

2013

Softw Syst Model

View full text Add to dashboard Cite

Self-explanatory user interfaces by model-driven engineering

Cited by 6 publications

References 15 publications

Generating contextual help for user interfaces from software requirements

Generating contextual help for user interfaces from software requirements

Adaptive Model-Driven User Interface Development Systems

Systematic literature review of the objectives, techniques, kinds, and architectures of models at runtime

Contact Info

Product

Resources

About