Code表示的相关文献

年份 文章 备注：

2021 Integrating Tree Path in Transformer for Code Representation 在 Transformer 结合语法树路径的代码表示方法
论文阅读笔记

2021 Unified Pre-training for Program Understanding and Generation 用于程序理解和生成的统一预训练
论文阅读笔记

2021 CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
论文阅读笔记

2021 A large-scale benchmark for few-shot program induction and synthesis 用于少量程序归纳和合成的大规模基准

2021 A Syntax-Guided Edit Decoder for Neural Program Repair 一种用于神经程序修复的语法引导编辑解码器

2021 CommitBERT: Commit Message Generation Using Pre-Trained Programming Language Model CommitBERT：使用预训练的编程语言模型生成提交消息

2021 Contrastive Learning for Source Code with Structural and Functional Properties 具有结构和功能特性的源代码的对比学习

2021 Disentangled Code Representation Learning for Multiple Programming Languages 多种编程语言的解开代码表示学习

2021 How could Neural Networks understand Programs? 神经网络如何理解程序？

2021 IdBench: Evaluating Semantic Representations of Identifier Names in Source Code IdBench：评估源代码中标识符名称的语义表示

2021 InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees InferCode：通过预测子树对代码表示进行自监督学习

2021 Language-Agnostic Representation Learning of Source Code from Structure and Context 源代码从结构和上下文的语言不可知表示学习

2021 Learning to Extend Program Graphs to Work-in-Progress Code 学习将程序图扩展到工作中的代码

2021 MulCode: A Multi-task Learning Approach for Source Code Understanding MulCode：一种用于源代码理解的多任务学习方法

2021 Multimodal Representation for Neural Code Search 神经代码搜索的多模态表示

2021 Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks 项目 CodeNet：用于学习多种编码任务的代码数据集的大规模 AI

2021 ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback ProtoTransformer：提供学生反馈的元学习方法

2021 PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from Code PSIMiner：一种从代码中挖掘丰富抽象语法树的工具

2021 Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations 通过语义保留转换进行代码检索和总结的自监督对比学习

2021 SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation SynCoBERT：用于代码表示的语法引导的多模态对比预训练

2021 Unsupervised Learning of General-Purpose Embeddings for Code Changes 通用嵌入代码更改的无监督学习

2021 What do pre-trained code models know about code? 预训练的代码模型对代码了解多少？

2020 A Structural Model for Contextual Code Changes 上下文代码更改的结构模型

2020 A Transformer-based Approach for Source Code Summarization 一种基于 Transformer 的源代码汇总方法
论文阅读笔记

2020 Adversarial Robustness for Code 代码的对抗性健壮性

2020 Blended, precise semantic program embeddings 混合的、精确的语义程序嵌入

2020 CC2Vec: Distributed Representations of Code Changes CC2Vec：代码更改的分布式表示

2020 Code and Named Entity Recognition in StackOverflow StackOverflow 中的代码和命名实体识别

2020 CodeBERT: A Pre-Trained Model for Programming and Natural Languages CodeBERT：用于编程和自然语言的预训练模型

2020 Compiler-based graph representations for deep learning models of code 代码深度学习模型的基于编译器的图形表示

2020 ComPy-Learn: A toolbox for exploring machine learning representations for compilers ComPy-Learn：用于探索编译器机器学习表示的工具箱

2020 Contrastive Code Representation Learning 对比代码表示学习

2020 Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree 使用图神经网络和流增强抽象语法树检测代码克隆

2020 Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks Devign：通过图神经网络学习综合程序语义来有效识别漏洞

2020 Embedding Java Classes with code2vec: Improvements from Variable Obfuscation 使用 code2vec 嵌入 Java 类：变量混淆的改进

2020 Evaluating Representation Learning of Code Changes for Predicting Patch Correctness in Program Repair 评估代码更改的表示学习以预测程序修复中的补丁正确性

2020 funcGNN: A Graph Neural Network Approach to Program Similarity funcGNN：程序相似性的图神经网络方法

2020 Global Relational Models of Source Code 源代码的全局关系模型

2020 GraphCodeBERT: Pre-training Code Representations with Data Flow GraphCodeBERT：使用数据流预训练代码表示

2020 Improving Code Search with Co-Attentive Representation Learning 使用协同表示学习改进代码搜索

2020 Learning Code-Query Interaction for Enhancing Code Searches 学习代码-查询交互以增强代码搜索

2020 Learning Semantic Program Embeddings with Graph Interval Neural Network 使用图间隔神经网络学习语义程序嵌入

2020 Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks 学习使用指令指针注意图神经网络执行程序

2020 Learning to Represent Programs with Heterogeneous Graphs 学习用异构图表示程序

2020 Learning to Update Natural Language Comments Based on Code Changes 学习根据代码更改更新自然语言注释

2020 Modular Tree Network for Source Code Representation Learning 用于源代码表示学习的模块化树网络

2020 Predicting Vulnerability in Large Codebases With Deep Code Representation 使用深度代码表示预测大型代码库中的漏洞

2020 ProGraML: Graph-based Deep Learning for Program Optimization and Analysis ProGraML：用于程序优化和分析的基于图的深度学习

2020 PSCS: A Path-based Neural Model for Semantic Code Search PSCS：用于语义代码搜索的基于路径的神经模型

2020 Recommendation of Move Method Refactoring Using Path-Based Representation of Code 使用基于路径的代码表示重构移动方法的建议

2020 SCELMo: Source Code Embeddings from Language Models SCELMo：来自语言模型的源代码嵌入

2020 Searching a Database of Source Codes Using Contextualized Code Search 使用上下文代码搜索来搜索源代码数据库

2020 Sequence Model Design for Code Completion in the Modern IDE 现代 IDE 中代码完成的序列模型设计

2020 Static Neural Compiler Optimization via Deep Reinforcement Learning 通过深度强化学习进行静态神经编译器优化

2020 Towards Learning Representations of Binary Executable Files for Security Tasks 面向安全任务的二进制可执行文件的学习表示

2019 A Literature Study of Embeddings on Source Code 源代码嵌入的文献研究

2019 A Novel Neural Source Code Representation based on Abstract Syntax Tree 一种基于抽象语法树的新型神经源代码表示

2019 Asm2Vec: Boosting Static Representation Robustness for Binary Clone Search against Code Obfuscation and Compiler Optimization Asm2Vec：针对代码混淆和编译器优化提高二进制克隆搜索的静态表示稳健性

2019 Capturing source code semantics via tree-based convolution over API-enhanced AST 通过 API 增强型 AST 上的基于树的卷积捕获源代码语义

2019 code2seq: Generating Sequences from Structured Representations of Code code2seq：从代码的结构化表示生成序列

2019 code2vec: Learning Distributed Representations of Code code2vec：学习代码的分布式表示

2019 Commit Message Generation for Source Code Changes 为源代码更改提交消息生成

2019 Commit2Vec: Learning Distributed Representations of Code Changes Commit2Vec：学习代码更改的分布式表示

2019 CORE: Automating Review Recommendation for Code Changes 核心：代码更改的自动化审查建议

2019 Import2vec - Learning Embeddings for Software Libraries Import2vec - 软件库的学习嵌入

2019 Improving Bug Detection via Context-Based Code Representation Learning and Attention-Based Neural Networks 通过基于上下文的代码表示学习和基于注意力的神经网络改进错误检测

2019 Inferring Javascript types using Graph Neural Networks 使用图神经网络推断 Javascript 类型

2019 Learning Execution through Neural Code Fusion 通过神经代码融合学习执行

2019 Learning Scalable and Precise Representation of Program Semantics 学习程序语义的可扩展和精确表示

2019 Learning to Represent Edits 学习表示编辑

2019 Learning to Sport and Refactor Inconsistent Method Names 学习运动和重构不一致的方法名

2019 Learning Uniform Semantic Features for Natural Language and Programming Language Globally, Locally and Sequentially 全局、局部和顺序地学习自然语言和编程语言的统一语义特征

2019 Mercem: Method Name Recommendation Based on Call Graph Embedding Mercem：基于调用图嵌入的方法名称推荐

2019 Method name suggestion with hierarchical attention networks 具有分层注意力网络的方法名称建议

2019 Mining Likely Analogical APIs across Third-Party Libraries via Large-Scale Unsupervised API Semantics Embedding 通过大规模无监督 API 语义嵌入在第三方库中挖掘可能的类比 API

2019 Multi-Modal Attention Network Learning for Semantic Source Code Retrieval 用于语义源代码检索的多模态注意力网络学习

2019 Natural Software Revisited 重新审视自然软件

2019 Neural Attribution for Semantic Bug-Localization in Student Programs 学生项目语义错误定位的神经归因

2019 Neural Reverse Engineering of Stripped Binaries 剥离二进制文件的神经逆向工程

2019 Neural-Network Guided Expression Transformation 神经网络引导的表达式转换

2019 On the Feasibility of Transfer-learning Code Smells using Deep Learning 使用深度学习迁移学习代码气味的可行性

2019 PathMiner : A Library for Mining of Path-Based Representations of Code PathMiner：用于挖掘基于路径的代码表示的库

2019 Program Classification Using Gated Graph Attention Neural Network for Online Programming Service 使用门控图注意力神经网络进行在线编程服务的程序分类

2019 SAR: Learning Cross-Language API Mappings with Little Knowledge SAR：用很少的知识学习跨语言API映射

2019 Semantic Source Code Models Using Identifier Embeddings 使用标识符嵌入的语义源代码模型

2019 Simulating Execution Time of Tensor Programs using Graph Neural Networks 使用图神经网络模拟张量程序的执行时间

2019 Towards Neural Decompilation 走向神经反编译

2019 TreeCaps: Tree-Structured Capsule Networks for Program Source Code Processing TreeCaps：用于程序源代码处理的树状结构胶囊网络

2018 A General Path-Based Representation for Predicting Program Properties 用于预测程序属性的基于路径的一般表示

2018 Automated Vulnerability Detection in Source Code Using Deep Representation Learning 使用深度表示学习在源代码中自动检测漏洞

2018 Bilateral Dependency Neural Networks for Cross-Language Algorithm Classification 用于跨语言算法分类的双边依赖神经网络

2018 Cross-Language Learning for Program Classification using Bilateral Tree-Based Convolutional Neural Networks 使用基于双边树的卷积神经网络进行程序分类的跨语言学习

2018 Deep Code Search 深度代码搜索

2018 Deep Learning Similarities from Different Representations of Source Code 来自不同源代码表示的深度学习相似性

2018 Deep Learning Type Inference 深度学习类型推断

2018 Hierarchical Learning of Cross-Language Mappings through Distributed Vector Representations for Code 通过代码的分布式向量表示进行跨语言映射的分层学习

2018 Intelligent code reviews using deep learning 使用深度学习进行智能代码审查

2018 Learning to Represent Programs with Graphs 学习用图形表示程序

2018 Neural Code Comprehension: A Learnable Representation of Code Semantics 神经代码理解：代码语义的可学习表示

2018 Open Vocabulary Learning on Source Code with a Graph-Structured Cache 使用图结构缓存对源代码进行开放式词汇学习

2018 Path-Based Function Embedding and its Application to Specification Mining 基于路径的函数嵌入及其在规范挖掘中的应用

2018 Polyglot Semantic Parsing in APIs API 中的多语言语义解析

2017 A Language Model for Statements of Software Code 软件代码语句的语言模型

2017 DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning DeepAM：将具有多模态序列的 API 迁移到序列学习

2017 End-to-end Deep Learning of Optimization Heuristics 优化启发式的端到端深度学习

2017 Exploring API Embedding for API Usages and Applications 探索 API 使用和应用程序的 API 嵌入

2017 Function Assistant: A Tool for NL Querying of APIs 功能助手：API NL 查询工具

2017 Learning Technical Correspondences in Technical Documentation 在技术文档中学习技术通信

2017 Learning to Align the Source Code to the Compiled Object Code 学习将源代码与编译后的目标代码对齐

2017 Neural Attribute Machines for Program Generation 用于程序生成的神经属性机

2017 Semantically enhanced software traceability using deep learning techniques 使用深度学习技术在语义上增强软件可追溯性

2017 SmartPaste: Learning to Adapt Source Code SmartPaste：学习适应源代码

2016 Automatically generating features for learning program analysis heuristics 自动生成学习程序分析启发式的特征

2016 Automatically Learning Semantic Features for Defect Prediction 缺陷预测的自动学习语义特征

2016 Bugram: bug detection with n-gram language models Bugram：使用 n-gram 语言模型进行错误检测

2016 Convolutional Neural Networks over Tree Structures for Programming Language Processing 用于编程语言处理的树结构上的卷积神经网络

2016 Learning API Usages from Bytecode: A Statistical Approach 从字节码中学习 API 用法：一种统计方法

2016 Mapping API Elements for Code Migration with Vector Representations 使用矢量表示映射代码迁移的 API 元素

2015 Exploring the Use of Deep Learning for Feature Location 探索使用深度学习进行特征定位

2015 Graph-based Statistical Language Model for Code 基于图的代码统计语言模型

2015 Learning Program Embeddings to Propagate Feedback on Student Code 用于传播学生代码反馈的学习计划嵌入

2015 Learning to Generate Pseudo-code from Source Code using Statistical Machine Translation 学习使用统计机器翻译从源代码生成伪代码

2015 Predicting Program Properties from “Big Code” 从“大代码”预测程序属性

2015 Toward Deep Learning Software Repositories 走向深度学习软件存储库

2015 Visualizing and Understanding Recurrent Networks 可视化和理解循环网络

2014 A system to grade computer programming skills using machine learning 一种使用机器学习对计算机编程技能进行评分的系统

2014 Building Program Vector Representations for Deep Learning 为深度学习构建程序向量表示

2014 Learning to Execute 学习执行

2013 Using Semantic Unification to Generate Regular Expressions from Natural Language 使用语义统一从自然语言生成正则表达式