Transferring Model-Driven visualizations concepts to Internet Of Things
Software is constantly evolving; this evolution is motivated by different reasons such as the obsolescence of a technology, the pressure of users, or the need to build a single coherent information system when merging companies. My research lies in the field of software modernization, a kind of evolution that refers to understand and evolve existing software assets to maintain a large part of their business value. In my talk, I present a Model-Driven Engineering approach to leverage modernization. The approach consists of two phases: i) Knowledge discovery of the existing system, ii) Transformative steps that move the as-is state to the to-be state. The first phase involves reverse engineering the existing software and presenting several different views to the users. The views help users to understand the legacy in an agnostic way and to take decisions that guide the transformative steps. I present results of the approach application into two projects that involves Colombian academic and industrial partners. This work has helped us to gain experience on Model-Driven visualizations that can be transferred to the Internet Of Things field where there are data understanding challenges. One can think about Model-Driven tools that produce metric-centered visualizations that helps one to discover aspects on the data emitted by devices. The reasons to use modeling in this field are: the power of models to unify inputs from different origins (i.e., devices) and the facility of building graphical editors on top of models. The talk ends with a practical work where participants will build a graphical editor based on a model.
Lecture at NEMO2016
Date/Time: Tuesday, July 26, 2016 at 11:30