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 …
A systematic literature review on the use of deep learning in software engineering research
An increasingly popular set of techniques adopted by software engineering (SE)
researchers to automate development tasks are those rooted in the concept of Deep …
researchers to automate development tasks are those rooted in the concept of Deep …
Text2mesh: Text-driven neural stylization for meshes
In this work, we develop intuitive controls for editing the style of 3D objects. Our framework,
Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which …
Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which …
A novel neural source code representation based on abstract syntax tree
Exploiting machine learning techniques for analyzing programs has attracted much
attention. One key problem is how to represent code fragments well for follow-up analysis …
attention. One key problem is how to represent code fragments well for follow-up analysis …
Detecting code clones with graph neural network and flow-augmented abstract syntax tree
Code clones are semantically similar code fragments pairs that are syntactically similar or
different. Detection of code clones can help to reduce the cost of software maintenance and …
different. Detection of code clones can help to reduce the cost of software maintenance and …
Retrieval-based neural source code summarization
Source code summarization aims to automatically generate concise summaries of source
code in natural language texts, in order to help developers better understand and maintain …
code in natural language texts, in order to help developers better understand and maintain …
Vuldeelocator: a deep learning-based fine-grained vulnerability detector
Automatically detecting software vulnerabilities is an important problem that has attracted
much attention from the academic research community. However, existing vulnerability …
much attention from the academic research community. However, existing vulnerability …
Functional code clone detection with syntax and semantics fusion learning
Clone detection of source code is among the most fundamental software engineering
techniques. Despite intensive research in the past decade, existing techniques are still …
techniques. Despite intensive research in the past decade, existing techniques are still …
A survey on machine learning techniques for source code analysis
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
Deep learning based software defect prediction
Software systems have become larger and more complex than ever. Such characteristics
make it very challengeable to prevent software defects. Therefore, automatically predicting …
make it very challengeable to prevent software defects. Therefore, automatically predicting …