Expert Systems With Applications 71 (2017) 125–137 Contents lists available at ScienceDirect Expert Systems With Applications journal homepage: www.elsevier.com/locate/eswa Automated reasoning based user interface Paweł Kapła ´ nski a,b , Alessandro Seganti a,∗ , Krzysztof Cie ´ sli ´ nski a , Aleksandra Chrabrowa a , Iwona Ługowska c a Cognitum, Warsaw, Poland b Gdansk University of Technology, Gdansk, Poland c Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology in Warsaw, Warsaw, Poland a r t i c l e i n f o Article history: Received 29 April 2016 Revised 20 November 2016 Accepted 22 November 2016 Available online 23 November 2016 Keywords: Model view controller Reasoning Semantic web OWL/RDF Model- driven engineering Decision support system User interface a b s t r a c t Motivation: The ability to directly trace how requirements are implemented in a software system is cru- cial 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 engi- neering 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 imple- mented 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. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction The development and maintenance of User Interfaces (UI) is an expensive process that is crucial for most of the businesses. Fur- thermore, with the spread of new interaction techniques such as touch or vocal input makes the implementation of a modern sys- tem UI becomes a critical part of the application lifecycle. More- over, the ability to directly trace how the requirements map to the software implementation is crucial for domains that require a high-level traceability (e.g. medicine, law, crisis management). Fur- thermore, all modern system should be simple not only to create but also to modify following many change-requests. ∗ Corresponding author. E-mail addresses: pawel.kaplanski@cognitum.eu (P. Kapła ´ nski), a.seganti@cognitum.eu (A. Seganti), k.cieslinski@cognitum.eu (K. Cie ´ sli ´ nski), a.klimek@cognitum.eu (A. Chrabrowa), iwonalugowska@coi.waw.pl (I. Ługowska). Model-Driven Engineering (MDE) answers to these questions. If we see a software system as a realization of an abstract model, then MDE can be understood as the way to transform the abstract model to the actual implementation of the system. In this article we present, developed by us, Automatic Reason- ing Based User Interface (ARBUI) approach together with its imple- mentation: the Semantic MVC. We show how we implemented the ARBUI approach and we give an example of a practical use where the Semantic MVC framework has been useful: the Clinical Deci- sion Support System for Gist Cancer (GIST-CDSS). 1.1. Methodology Selected research methodology combines Literature Review and Pilot Study with Action Research (AR), that is intended to ex- plore improvements of the specific process. AR is a cycle of actions (Susman & Evered, 1978) presented in Fig. 1. http://dx.doi.org/10.1016/j.eswa.2016.11.033 0957-4174/© 2016 Elsevier Ltd. All rights reserved.