  Traditional software engineering programming paradigms are mostly object or
procedure oriented, driven by deterministic algorithms. With the advent of deep
learning and cognitive sciences there is an emerging trend for data-driven
programming, creating a shift in the programming paradigm among the software
engineering communities. Visualizing and interpreting the execution of a
current large scale data-driven software development is challenging. Further,
for deep learning development there are many libraries in multiple programming
languages such as TensorFlow (Python), CAFFE (C++), Theano (Python), Torch
(Lua), and Deeplearning4j (Java), driving a huge need for interoperability
across libraries.

Software Engineering