Papers Code Completion
“Code Completion” 태그가 달린 논문 280편 · 필터 해제
From Copilot to Pilot: Towards AI Supported Software Development
AI-supported programming has arrived, as shown by the introduction and successes of large language models for code, such as Copilot/Codex (Github/OpenAI) and AlphaCode (DeepMind). Above human average performance on progr…
Code CompletionNot what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
Large Language Models (LLMs) are increasingly being integrated into various applications. The functionalities of recent LLMs can be flexibly modulated via natural language prompts. This renders them susceptible to target…
Code CompletionComputer SecurityInstruction FollowingRetrievalLearning Deep Semantics for Test Completion
Writing tests is a time-consuming yet essential task during software development. We propose to leverage recent advances in deep learning for text and code generation to assist developers in writing tests. We formalize t…
Code CompletionCode GenerationGeneration Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions
Large-scale generative models enabled the development of AI-powered code completion tools to assist programmers in writing code. However, much like other AI-powered tools, AI-powered code completions are not always accur…
Code CompletionAutomating Code-Related Tasks Through Transformers: The Impact of Pre-training
Transformers have gained popularity in the software engineering (SE) literature. These deep learning models are usually pre-trained through a self-supervised objective, meant to provide the model with basic knowledge abo…
Bug fixingCode CompletionCode SummarizationLanguage Modelling+1Execution-based Code Generation using Deep Reinforcement Learning
The utilization of programming language (PL) models, pre-trained on large-scale code corpora, as a means of automating software engineering processes has demonstrated considerable potential in streamlining various code g…
Code CompletionCode GenerationCode TranslationDeep Reinforcement Learning+6Serenity: Library Based Python Code Analysis for Code Completion and Automated Machine Learning
Dynamically typed languages such as Python have become very popular. Among other strengths, Python's dynamic nature and its straightforward linking to native code have made it the de-facto language for many research area…
Code CompletionUnveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities
Past research has examined how well these models grasp code syntax, yet their understanding of code semantics still needs to be explored. We extensively analyze seven code models to investigate how code models represent …
Code CompletionCode SearchLanguage ModellingProgram SynthesisCoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context
While pre-trained language models (LM) for code have achieved great success in code completion, they generate code conditioned only on the contents within the file, i.e., in-file context, but ignore the rich semantics in…
Code CompletionMultiCoder: Multi-Programming-Lingual Pre-Training for Low-Resource Code Completion
Code completion is a valuable topic in both academia and industry. Recently, large-scale mono-programming-lingual (MonoPL) pre-training models have been proposed to boost the performance of code completion. However, the …
Code CompletionMixture-of-ExpertsSyntax-Aware On-the-Fly Code Completion
Code completion aims to help improve developers' productivity by suggesting the next code tokens from a given context. Various approaches have been proposed to incorporate abstract syntax tree (AST) information for model…
Code CompletionMulti-lingual Evaluation of Code Generation Models
We present new benchmarks on evaluation code generation models: MBXP and Multilingual HumanEval, and MathQA-X. These datasets cover over 10 programming languages and are generated using a scalable conversion framework th…
Code CompletionCode GenerationCode TranslationHumanEval+1Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming
Code-recommendation systems, such as Copilot and CodeWhisperer, have the potential to improve programmer productivity by suggesting and auto-completing code. However, to fully realize their potential, we must understand …
Code CompletionRecommendation SystemsText and Patterns: For Effective Chain of Thought, It Takes Two to Tango
The past decade has witnessed dramatic gains in natural language processing and an unprecedented scaling of large language models. These developments have been accelerated by the advent of few-shot techniques such as cha…
Code CompletioncounterfactualText GenerationDon't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems
Currently, large pre-trained language models are widely applied in neural code completion systems. Though large code models significantly outperform their smaller counterparts, around 70\% of displayed code completions f…
Code CompletionMetaTPTrans: A Meta Learning Approach for Multilingual Code Representation Learning
Representation learning of source code is essential for applying machine learning to software engineering tasks. Learning code representation from a multilingual source code dataset has been shown to be more effective th…
Code CompletionCode SummarizationMeta-LearningRepresentation LearningHierarchyNet: Learning to Summarize Source Code with Heterogeneous Representations
We propose a novel method for code summarization utilizing Heterogeneous Code Representations (HCRs) and our specially designed HierarchyNet. HCRs effectively capture essential code features at lexical, syntactic, and se…
Clone DetectionCode ClassificationCode CompletionCode SummarizationAll You Need Is Logs: Improving Code Completion by Learning from Anonymous IDE Usage Logs
In this work, we propose an approach for collecting completion usage logs from the users in an IDE and using them to train a machine learning based model for ranking completion candidates. We developed a set of features …
AllCode CompletionProductivity Assessment of Neural Code Completion
Neural code synthesis has reached a point where snippet generation is accurate enough to be considered for integration into human software development workflows. Commercial products aim to increase programmers' productiv…
Code CompletionReACC: A Retrieval-Augmented Code Completion Framework
Code completion, which aims to predict the following code token(s) according to the code context, can improve the productivity of software development. Recent work has proved that statistical language modeling with trans…
Code CompletionLanguage ModelingLanguage ModellingRetrieval