Codetrans: Towards cracking the language of silicon's code through self-supervised deep learning and high performance computing

A Elnaggar, W Ding, L Jones, T Gibbs, T Feher… - arxiv preprint arxiv …, 2021 - arxiv.org
Currently, a growing number of mature natural language processing applications make
people's life more convenient. Such applications are built by source code-the language in …

How to improve deep learning for software analytics: (a case study with code smell detection)

R Yedida, T Menzies - Proceedings of the 19th International Conference …, 2022 - dl.acm.org
To reduce technical debt and make code more maintainable, it is important to be able to
warn programmers about code smells. State-of-the-art code small detectors use deep …

A deep intelligent framework for software risk prediction using improved firefly optimization

SK Pemmada, J Nayak, B Naik - Neural Computing and Applications, 2023 - Springer
For the success of a software project, early and precise discrimination of software
requirement risks are essential. Researchers have suggested several predictive methods …

Old but Gold: Reconsidering the value of feedforward learners for software analytics

R Yedida, X Yang, T Menzies - arxiv preprint arxiv:2101.06319, 2021 - arxiv.org
There has been an increased interest in the use of deep learning approaches for software
analytics tasks. State-of-the-art techniques leverage modern deep learning techniques such …

[PDF][PDF] Exploring the possibilities of applying transfer learning methods for natural language processing in software development

W Ding - Master's thesis, Dept. Comput. Sci., Technische …, 2021 - wwwmatthes.in.tum.de
Nowadays, we have a growing number of mature applications in the field of natural
language processing (NLP), especially natural language understanding (NLU) and …