2019/11/27 by Bianca Iancu, Gabriele Mazzola, Iancu, Bianca +5
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Software Engineering Research #Software Testing and Debugging Techniques #Topic Modeling #cs.LG #stat.ML
paper · pdf · doi:10.48550/arxiv.1911.12224
arxiv created 2019/11/27 · openalex publication_date 2019/11/27 · arxiv updated 2019/11/28 · openalex created_date 2019/12/05 · openalex updated_date 2026/07/28
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.