Automated reasoning based user interface. (1st April 2017) - Kapłański, Paweł
Highlights: Automatic generation of user interfaces from domain knowledge: ARBUI. Practical implementation of the proposed architecture (ARBUI): the Semantic MVC. Tested our approach in a pilot project at the Oncology Center in Warsaw. Abstract: Motivation : The ability to directly trace how requirements are implemented in a software system is crucial in domains that require a high level of trust (e.g. medicine, law, crisis management). This paper describes an approach that allows a high level of traceability to be achieved with model-driven engineering supported by automated reasoning. The paper gives an introduction to the novel, automated user interface synthesis in which a set of requirements is automatically translated into a working application. It is presented as a generalization of the current state of the art model-driven approaches both from the conceptual perspective as well as the concrete implementation is discussed together with its advantages like the alignment of business logic with the application and ease of adaptability. It also presents how a high level of traceability can be obtained if runtime support of automated reasoning over models is applied. Results : We have defined the Automated Reasoning-Based User Interface (ARBUI) approach and implemented a framework for application programming that follows our definition. The framework, called Semantic MVC, is based on model-driven engineering principles enhanced with W3C standards for the semantic web. We will present the general architecture and main ideas underlying our approach and framework. Finally, we will present a practical application of the Semantic MVC that we created in the medical domain as a Clinical Decision Support System for GIST cancer in cooperation with the Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology in Warsaw. The discussed expert system allows the expert to directly modify the executable knowledge on the fly, making the overall system cost effective.