A survey on deep learning for software engineering
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 …
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
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 …
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 …
domains and are using traction within software engineering research as well. Such models …
Machine/deep learning for software engineering: A systematic literature review
Since 2009, the deep learning revolution, which was triggered by the introduction of
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …
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
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 …
security. Different forms of network attacks have been discovered and they continue to …
Representation learning for stack overflow posts: How far are we?
The tremendous success of Stack Overflow has accumulated an extensive corpus of
software engineering knowledge, thus motivating researchers to propose various solutions …
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
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 …
intentionally introduced and remarked by code comments. Those technical debts reduce the …
Memorization and generalization in neural code intelligence models
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 …
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?
APIs (Application Programming Interfaces) are reusable software libraries and are building
blocks for modern rapid software development. Previous research shows that programmers …
blocks for modern rapid software development. Previous research shows that programmers …
Post2vec: Learning distributed representations of Stack Overflow posts
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 …
desired information or aid various downstream software engineering tasks. A common step …