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

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.