A survey on deep learning for software engineering

Y Yang, X Xia, D Lo, J Grundy - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

Analysis of community question‐answering issues via machine learning and deep learning: State‐of‐the‐art review

PK Roy, S Saumya, JP Singh… - CAAI Transactions on …, 2023 - Wiley Online Library
Over the last couple of decades, community question‐answering sites (CQAs) have been a
topic of much academic interest. Scholars have often leveraged traditional machine learning …

On the validity of pre-trained transformers for natural language processing in the software engineering domain

J Von der Mosel, A Trautsch… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Transformers are the current state-of-the-art of natural language processing in many
domains and are using traction within software engineering research as well. Such models …

Machine/deep learning for software engineering: A systematic literature review

S Wang, L Huang, A Gao, J Ge, T Zhang… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Since 2009, the deep learning revolution, which was triggered by the introduction of
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …

A deep learning-based smart framework for cyber-physical and satellite system security threats detection

I Ashraf, M Narra, M Umer, R Majeed, S Sadiq, F Javaid… - Electronics, 2022 - mdpi.com
An intrusion detection system serves as the backbone for providing high-level network
security. Different forms of network attacks have been discovered and they continue to …

Representation learning for stack overflow posts: How far are we?

J He, X Zhou, B Xu, T Zhang, K Kim, Z Yang… - ACM Transactions on …, 2024 - dl.acm.org
The tremendous success of Stack Overflow has accumulated an extensive corpus of
software engineering knowledge, thus motivating researchers to propose various solutions …

How far have we progressed in identifying self-admitted technical debts? A comprehensive empirical study

Z Guo, S Liu, J Liu, Y Li, L Chen, H Lu… - ACM Transactions on …, 2021 - dl.acm.org
Background. Self-admitted technical debt (SATD) is a special kind of technical debt that is
intentionally introduced and remarked by code comments. Those technical debts reduce the …

Memorization and generalization in neural code intelligence models

MRI Rabin, A Hussain, MA Alipour… - Information and Software …, 2023 - Elsevier
Abstract Context: Deep Neural Networks (DNNs) are increasingly being used in software
engineering and code intelligence tasks. These are powerful tools that are capable of …

Aspect-based api review classification: How far can pre-trained transformer model go?

C Yang, B Xu, JY Khan, G Uddin, D Han… - … on Software Analysis …, 2022 - ieeexplore.ieee.org
APIs (Application Programming Interfaces) are reusable software libraries and are building
blocks for modern rapid software development. Previous research shows that programmers …

Post2vec: Learning distributed representations of Stack Overflow posts

B Xu, T Hoang, A Sharma, C Yang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Past studies have proposed solutions that analyze Stack Overflow content to help users find
desired information or aid various downstream software engineering tasks. A common step …