Towards a model-driven approach for multiexperience AI-based user interfaces

Abstract

Software systems start to include other types of interfaces beyond the “traditional” Graphical-User Interfaces (GUIs). In particular, Conversational User Interfaces (CUIs) such as chat and voice are becoming more and more popular. These new types of interfaces embed smart natural language processing components to understand user requests and respond to them. To provide an integrated user experience all the user interfaces in the system should be aware of each other and be able to collaborate. This is what is known as a multiexperience User Interface. Despite their many benefits, multiexperience UIs are challenging to build. So far CUIs are created as standalone components using a platform-dependent set of libraries and technologies. This raises significant integration, evolution and maintenance issues. This paper explores the application of model-driven techniques to the development of software applications embedding a multiexperience User Interface. We will discuss how raising the abstraction level at which these interfaces are defined enables a faster development and a better deployment and integration of each interface with the rest of the software system and the other interfaces with whom it may need to collaborate. In particular, we propose a new Domain Specific Language (DSL) for specifying several types of CUIs and show how this DSL can be part of an integrated modeling environment able to describe the interactions between the modeled CUIs and the other models of the system (including the models of the GUI). We will use the standard Interaction Flow Modeling Language (IFML) as an example “host” language.

Towards Access Control Models for Conversational User Interfaces

“…The authorization policy is expressed via a policy language. To this end, this paper we propose to extend a generic CUI language [15] with new modeling primitives adding access-control semantics to CUIs. As any DSL, this extended access-control-CUI DSL is defined through two main components [10]: (i) an abstract syntax (metamodel) which specifies the language concepts and their relationships, and (ii) a concrete syntax which provides a specific (textual or graphical) representation to specify models conforming to the abstract syntax.…”

“…The CUI-specific metamodel part (coloured in grey in Fig. 2) is a simplified version from the metamodel previously defined by the authors in [15] and describes the set of concepts used for modeling the intent definitions of a bot and its execution logic. The main elements of this metamodel are:…”

“…This limitation is shared by proposals focusing on chatbot definition languages, such as [6,14,15], which do not include modeling primitives to define the access-control policies even if modeling of access-control policies is a subject with a long tradition in the MDE community [3], with some notable examples like SecureUML [13] which extends UML with an RBAC metamodel that serves as inspiration for our own proposal. To sum up, we believe ours is the first approach to integrate access-control as first-class citizen in a bot definition language.…”

“…This facilitates the generation of such secure CUIs on top of different development platforms. In particular, we extend our generic CUI language [15] with new access-control modeling primitives adapted to the CUI domain and show how this extended models can be enforced as part of a policy evaluation component. As an example, we discuss such implementation on top of the Xatkit open source framework [6].…”

Towards Designing and Generating User Interfaces by Using Expert Knowledge

“…Moreover, the proposed model-based approach covers the description of omni-channel UIs with its semantic and syntax that are specified using meta-models and JSON, respectively. Planas et al [Planas et al, 2021] provide a model-based approach for conversational UIs supporting the design of each interface. They make use of an existing modeling language for UI specification.…”