Papers Code Completion
“Code Completion” 태그가 달린 논문 280편 · 필터 해제
Towards Full-line Code Completion with Neural Language Models
A code completion system suggests future code elements to developers given a partially-complete code snippet. Code completion is one of the most useful features in Integrated Development Environments (IDEs). Currently, m…
Code CompletionGraphCodeBERT: Pre-training Code Representations with Data Flow
Pre-trained models for programming language have achieved dramatic empirical improvements on a variety of code-related tasks such as code search, code completion, code summarization, etc. However, existing pre-trained mo…
Clone DetectionCode CompletionCode SearchCode Summarization+6You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion
Code autocompletion is an integral feature of modern code editors and IDEs. The latest generation of autocompleters uses neural language models, trained on public open-source code repositories, to suggest likely (not jus…
Code CompletionData PoisoningModel PoisoningIntelliCode Compose: Code Generation Using Transformer
In software development through integrated development environments (IDEs), code completion is one of the most widely used features. Nevertheless, majority of integrated development environments only support completion o…
Code CompletionCode GenerationDecoderLambdaNet: Probabilistic Type Inference using Graph Neural Networks
As gradual typing becomes increasingly popular in languages like Python and TypeScript, there is a growing need to infer type annotations automatically. While type annotations help with tasks like code completion and sta…
Code CompletionGraph Neural NetworkVocal Bursts Type PredictionFast and Memory-Efficient Neural Code Completion
Code completion is one of the most widely used features of modern integrated development environments (IDEs). While deep learning has made significant progress in the statistical prediction of source code, state-of-the-a…
Code CompletionLanguage ModellingLearning-To-RankRerankingCode Completion using Neural Attention and Byte Pair Encoding
In this paper, we aim to do code completion based on implementing a Neural Network from Li et. al.. Our contribution is that we use an encoding that is in-between character and word encoding called Byte Pair Encoding (BP…
Code CompletionSequence Model Design for Code Completion in the Modern IDE
Code completion plays a prominent role in modern integrated development environments (IDEs). Machine learning has become ubiquitous in analogous natural language writing and search software, surfacing more relevant autoc…
Code CompletionLanguage ModelingLanguage ModellingvalidAdversarial Robustness for Code
Machine learning and deep learning in particular has been recently used to successfully address many tasks in the domain of code such as finding and fixing bugs, code completion, decompilation, type inference and many ot…
Adversarial RobustnessBIG-bench Machine LearningCode CompletionPythia: AI-assisted Code Completion System
In this paper, we propose a novel end-to-end approach for AI-assisted code completion called Pythia. It generates ranked lists of method and API recommendations which can be used by software developers at edit time. The …
Code CompletionLanguage ModelingLanguage ModellingDeepVS: An Efficient and Generic Approach for Source Code Modeling Usage
The source code suggestions provided by current IDEs are mostly dependent on static type learning. These suggestions often end up proposing irrelevant suggestions for a peculiar context. Recently, deep learning-based app…
Code CompletionStructural Language Models of Code
We address the problem of any-code completion - generating a missing piece of source code in a given program without any restriction on the vocabulary or structure. We introduce a new approach to any-code completion that…
C++ codeCode CompletionCode GenerationLanguage Modeling+1A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning
Code completion, one of the most useful features in the Integrated Development Environments (IDEs), can accelerate software development by suggesting the libraries, APIs, and method names in real-time. Recent studies hav…
Code CompletionLanguage ModellingMulti-Task LearningUser-Interactive Machine Learning Model for Identifying Structural Relationships of Code Features
Traditional machine learning based intelligent systems assist users by learning patterns in data and making recommendations. However, these systems are limited in that the user has little means of understanding the ratio…
BIG-bench Machine LearningCode CompletionDecision MakingCodeGRU: Context-aware Deep Learning with Gated Recurrent Unit for Source Code Modeling
Recently deep learning based Natural Language Processing (NLP) models have shown great potential in the modeling of source code. However, a major limitation of these approaches is that they take source code as simple tok…
Code CompletionCode GenerationLanguage ModellingEclipse CDT code analysis and unit testing
In this paper we look at the Eclipse IDE and its support for CDT (C/C++ Development Tools). Eclipse is an open source IDE and supports a variety of programming languages including plugin functionality. Eclipse supports t…
Code CompletionCode GenerationOpen Vocabulary Learning on Source Code with a Graph-Structured Cache
Machine learning models that take computer program source code as input typically use Natural Language Processing (NLP) techniques. However, a major challenge is that code is written using an open, rapidly changing vocab…
Code CompletionGraph Neural NetworkDynamic Neural Program Embeddings for Program Repair
Neural program embeddings have shown much promise recently for a variety of program analysis tasks, including program synthesis, program repair, code completion, and fault localization. However, most existing program emb…
Code CompletionFault localizationProgram RepairProgram SynthesisCode Completion with Neural Attention and Pointer Networks
Intelligent code completion has become an essential research task to accelerate modern software development. To facilitate effective code completion for dynamically-typed programming languages, we apply neural language m…
Code CompletionAugur: a Modeling Language for Data-Parallel Probabilistic Inference
It is time-consuming and error-prone to implement inference procedures for each new probabilistic model. Probabilistic programming addresses this problem by allowing a user to specify the model and having a compiler auto…
Code CompletionGPUProbabilistic Programming