Papers Code Summarization
“Code Summarization” 태그가 달린 논문 163편 · 필터 해제
Automating 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+1Exploring Data Augmentation for Code Generation Tasks
Advances in natural language processing, such as transfer learning from pre-trained language models, have impacted how models are trained for programming language tasks too. Previous research primarily explored code pre-…
Code GenerationCode SummarizationCode TranslationData Augmentation+1A Survey on Pretrained Language Models for Neural Code Intelligence
As the complexity of modern software continues to escalate, software engineering has become an increasingly daunting and error-prone endeavor. In recent years, the field of Neural Code Intelligence (NCI) has emerged as a…
Code SummarizationSurveyERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages
Software engineers working with the same programming language (PL) may speak different natural languages (NLs) and vice versa, erecting huge barriers to communication and working efficiency. Recent studies have demonstra…
Code SummarizationLanguage ModelingLanguage ModellingText Generation+1CLAWSAT: Towards Both Robust and Accurate Code Models
We integrate contrastive learning (CL) with adversarial learning to co-optimize the robustness and accuracy of code models. Different from existing works, we show that code obfuscation, a standard code transformation ope…
Code GenerationCode SummarizationContrastive LearningSelf-Supervised LearningPre-Training Representations of Binary Code Using Contrastive Learning
Binary code analysis and comprehension is critical to applications in reverse engineering and computer security tasks where source code is not available. Unfortunately, unlike source code, binary code lacks semantics and…
Code SummarizationComputer SecurityContrastive LearningRepresentation Learning+1Boosting Code Summarization by Embedding Code Structures
Recent research on code summarization relies on the structural information from the abstract syntax tree (AST) of source codes. It is, however, questionable whether it is the most effective to use AST for expressing the …
Code SummarizationGraph EmbeddingExtreme Multi-Domain, Multi-Task Learning With Unified Text-to-Text Transfer Transformers
Text-to-text transformers have shown remarkable success in the task of multi-task transfer learning, especially in natural language processing (NLP). However, while there have been several attempts to train transformers …
Code SummarizationMulti-Task LearningTransfer LearningTowards Code Summarization of APIs Based on Unofficial Documentation Using NLP Techniques
Each programming language comes with official documentation to guide developers with APIs, methods, and classes. However, in some cases, official documentation is not an efficient way to get the needed information. As a …
Code SummarizationNo More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence
Pre-trained models have been shown effective in many code intelligence tasks. These models are pre-trained on large-scale unlabeled corpus and then fine-tuned in downstream tasks. However, as the inputs to pre-training a…
Code SummarizationCode TranslationFew-shot training LLMs for project-specific code-summarization
Very large language models (LLMs), such as GPT-3 and Codex have achieved state-of-the-art performance on several natural-language tasks, and show great promise also for code. A particularly exciting aspect of LLMs is the…
Code SummarizationFew-Shot LearningZero-Shot LearningEvaluation of Contrastive Learning with Various Code Representations for Code Clone Detection
Code clones are pairs of code snippets that implement similar functionality. Clone detection is a fundamental branch of automatic source code comprehension, having many applications in refactoring recommendation, plagiar…
Clone DetectionCode SummarizationContrastive LearningAn Extractive-and-Abstractive Framework for Source Code Summarization
(Source) Code summarization aims to automatically generate summaries/comments for a given code snippet in the form of natural language. Such summaries play a key role in helping developers understand and maintain source …
Code SummarizationMachine TranslationRetrievalSource Code SummarizationMetaTPTrans: 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 LearningLearning code summarization from a small and local dataset
Foundation models (e.g., CodeBERT, GraphCodeBERT, CodeT5) work well for many software engineering tasks. These models are pre-trained (using self-supervision) with billions of code tokens, and then fine-tuned with hundre…
Code SummarizationTime SeriesTime Series AnalysisHierarchyNet: 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 SummarizationSummarize and Generate to Back-translate: Unsupervised Translation of Programming Languages
Back-translation is widely known for its effectiveness in neural machine translation when there is little to no parallel data. In this approach, a source-to-target model is coupled with a target-to-source model trained i…
Code GenerationCode SummarizationMachine TranslationTranslationA Neural Network Architecture for Program Understanding Inspired by Human Behaviors
Program understanding is a fundamental task in program language processing. Despite the success, existing works fail to take human behaviors as reference in understanding programs. In this paper, we consider human behavi…
Clone DetectionCode SummarizationGraph Neural NetworkModeling Hierarchical Syntax Structure with Triplet Position for Source Code Summarization
Automatic code summarization, which aims to describe the source code in natural language, has become an essential task in software maintenance. Our fellow researchers have attempted to achieve such a purpose through vari…
Code SummarizationGraph Neural NetworkPositionSource Code Summarization+1GypSum: Learning Hybrid Representations for Code Summarization
Code summarization with deep learning has been widely studied in recent years. Current deep learning models for code summarization generally follow the principle in neural machine translation and adopt the encoder-decode…
Code SummarizationDecoderDeep LearningGraph Attention+3