Abstract: Generative adversarial neural networks are good in producing images automatically from noise. These images are becoming more and more realistic. The above mechanism has been extended to apply to generation of a user interface such as a webpage. But the starting point would be a coarse arrangement of required UI elements. A user specifies user interface elements on a coarse grid layout. The finer geometry of the UI elements which is both pleasing and familiar to look at, would be generated by a neural network. A particular variety of generative adversarial networks called SR-GAN is very well suited to this. The neural network would be trained on existing most popular web sites to understand the way coarse arrangement of web page elements correspond to actual dimensions of those elements, the same way, a high resolution image could be generated from low resolution image.

Abstract: A method, program and a graphical user interface to navigate through different watch points at which a variable changes its value and look at instantaneous values of all the variables in the same stack at that point of time, while hovering on the code on a graphical integrated development environment. This method may also include a method to determine which data to store based on anomalies on both the data and the times at which this data was written.