  One of the best ways for developers to test and improve their skills in a fun
and challenging way are programming challenges, offered by a plethora of
websites. For the inexperienced ones, some of the problems might appear too
challenging, requiring some suggestions to implement a solution. On the other
hand, tagging problems can be a tedious task for problem creators. In this
paper, we focus on automating the task of tagging a programming challenge
description using machine and deep learning methods. We observe that the deep
learning methods implemented outperform well-known IR approaches such as
tf-idf, thus providing a starting point for further research on the task.
