Overview of Deep Learning-Based Code Representation and Its Applications

Overview of Deep Learning-Based Code Representation and Its Applications

The analysis and inference of program play an important role in software development, maintenance and migration. How to efficiently obtain high quality information from program code has become a hot research topic. In recent years, a large number of researchers have introduced the deep learning-base...

Fuld beskrivelse

Bibliografiske detaljer
Hovedforfatter:	ZHANG Xiangping, LIU Jianxun
Format:	Article
Sprog:	zho
Udgivet:	Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 2022-09-01
Serier:	Jisuanji kexue yu tansuo
Fag:	\|code representation\|representation learning\|software engineering\|code analysis\|deep learning
Online adgang:	http://fcst.ceaj.org/fileup/1673-9418/PDF/2110073.pdf

Lignende værker

Code Readability Assessment Method Based on Multidimensional Features and Hybrid Neural Networks
af: MI Qing, GUO Li-min, CHEN Jun-cheng
Udgivet: (2021-12-01)

Learning Sentence-Level Representations with Predictive Coding
af: Vladimir Araujo, et al.
Udgivet: (2023-01-01)

Code Aggregate Graph: Effective Representation for Graph Neural Networks to Detect Vulnerable Code
af: Hoang Viet Nguyen, et al.
Udgivet: (2022-01-01)

Enhanced representation learning with temporal coding in sparsely spiking neural networks
af: Adrien Fois, et al.
Udgivet: (2023-11-01)

Discrete Infomax Codes for Supervised Representation Learning
af: Yoonho Lee, et al.
Udgivet: (2022-04-01)

Software Vulnerability Detection Using Informed Code Graph Pruning
af: Joseph Gear, et al.
Udgivet: (2023-01-01)

Deep Learning-Based Software Defect Prediction via Semantic Key Features of Source Code—Systematic Survey
af: Ahmed Abdu, et al.
Udgivet: (2022-08-01)

An overview on data representation learning: From traditional feature learning to recent deep learning
af: Guoqiang Zhong, et al.
Udgivet: (2016-12-01)

Minimal State-Space Representation of Convolutional Product Codes
af: Joan-Josep Climent, et al.
Udgivet: (2021-06-01)

FCNN: Simple neural networks for complex code tasks
af: Xuekai Sun, et al.
Udgivet: (2024-02-01)

Gender Representation of Code Switching in Students' Presentation: How Do They Differ?
af: Muhamad Kenzo Akbar, et al.
Udgivet: (2024-07-01)

An Investigation of the Linguistic Complexity of IELTS Writing Topics Based on the Levels of Discourse Representation and the Degree of Meaning Coding
af: Mohammad Zare, et al.
Udgivet: (2021-01-01)

RepFTI: Representation-Fused Function-Type Inference for Vehicular Secure Software Systems
af: Xiaoyu Yi, et al.
Udgivet: (2024-05-01)

On the State Approach Representations of Convolutional Codes over Rings of Modular Integers
af: Ángel Luis Muñoz Castañeda, et al.
Udgivet: (2021-11-01)

Binary Code Representation With Well-Balanced Instruction Normalization
af: Hyungjoon Koo, et al.
Udgivet: (2023-01-01)

Network Representation Learning
af: Weizheng Chen, et al.
Udgivet: (2015-06-01)

Integrated Sparse Coding With Graph Learning for Robust Data Representation
af: Yupei Zhang, et al.
Udgivet: (2020-01-01)

Descriptive Analysis of the Graphic Representations of Science Textbooks
af: Myint Swe Khine, et al.
Udgivet: (2017-12-01)

Hierarchical Sparse Coding of Objects in Deep Convolutional Neural Networks
af: Xingyu Liu, et al.
Udgivet: (2020-12-01)

Image restoration based on sparse representation using feature classification learning
af: Minhui Chang, et al.
Udgivet: (2020-11-01)

An Efficient and Scalable Platform for Java Source Code Analysis Using Overlaid Graph Representations
af: Oscar Rodriguez-Prieto, et al.
Udgivet: (2020-01-01)

Context-based intelligent recommendation for code reuse
af: Xin PENG, et al.
Udgivet: (2021-01-01)

An Ontology-Based Approach to Reduce the Negative Impact of Code Smells in Software Development Projects
af: Ivian L. Castellano, et al.
Udgivet: (2023-01-01)

Apk2vec : semi-supervised multi-view representation learning for profiling Android applications
af: Narayanan, Annamalai, et al.
Udgivet: (2020)

Assessment of Software Vulnerability Contributing Factors by Model-Agnostic Explainable AI
af: Ding Li, et al.
Udgivet: (2024-05-01)

Deep Learning-Based Compressed Domain Multimedia for Man and Machine: A Taxonomy and Application to Point Cloud Classification
af: Abdelrahman Seleem, et al.
Udgivet: (2023-01-01)

On Matrix Representation of Extension Field GF(<i>p<sup>L</sup></i>) and Its Application in Vector Linear Network Coding
af: Hanqi Tang, et al.
Udgivet: (2024-09-01)

Deep Forest and Pruned Syntax Tree-Based Classification Method for Java Code Vulnerability
af: Jiaman Ding, et al.
Udgivet: (2023-01-01)

Securing Code With Context: Enhancing Vulnerability Detection Through Contextualized Graph Representations
af: Muhammad Fakhrur Rozi, et al.
Udgivet: (2024-01-01)

CPPVec: an accurate coding potential predictor based on a distributed representation of protein sequence
af: Chao Wei, et al.
Udgivet: (2023-05-01)

Explaining Cognitive Phenomena with Internal Representations: A Mechanistic Perspective
af: Gładziejewski Paweł
Udgivet: (2015-03-01)

Fret: Functional Reinforced Transformer With BERT for Code Summarization
af: Ruyun Wang, et al.
Udgivet: (2020-01-01)

Local minimization of prediction errors drives learning of invariant object representations in a generative network model of visual perception
af: Matthias Brucklacher, et al.
Udgivet: (2023-09-01)

A Review of Disentangled Representation Learning for Remote Sensing Data
af: Mi Wang, et al.
Udgivet: (2022-12-01)

Survey on static software vulnerability detection for source code
af: Zhen LI, et al.
Udgivet: (2019-02-01)

Unsupervised Representation Learning with Task-Agnostic Feature Masking for Robust End-to-End Speech Recognition
af: June-Woo Kim, et al.
Udgivet: (2023-01-01)

Unsupervised Facial Action Representation Learning by Temporal Prediction
af: Chongwen Wang, et al.
Udgivet: (2022-03-01)

Network Representation Learning: From Traditional Feature Learning to Deep Learning
af: Ke Sun, et al.
Udgivet: (2020-01-01)

Intentional spatial coding of responses under multiple action effect situations
af: Loïc P. Heurley, et al.
Udgivet: (2023-08-01)

“Paper, Meet Code”: A Deep Learning Approach to Linking Scholarly Articles With GitHub Repositories
af: Prahyat Puangjaktha, et al.
Udgivet: (2024-01-01)