Papers Code Summarization
“Code Summarization” 태그가 달린 논문 163편 · 필터 해제
On the Transferability of Pre-trained Language Models for Low-Resource Programming Languages
A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves higher performance as opposed to using a cor…
Code SearchCode SummarizationAn Exploratory Study on Code Attention in BERT
Many recent models in software engineering introduced deep neural models based on the Transformer architecture or use transformer-based Pre-trained Language Models (PLM) trained on code. Although these models achieve the…
Clone DetectionCode SummarizationM2TS: Multi-Scale Multi-Modal Approach Based on Transformer for Source Code Summarization
Source code summarization aims to generate natural language descriptions of code snippets. Many existing studies learn the syntactic and semantic knowledge of code snippets from their token sequences and Abstract Syntax …
Code SummarizationSource Code SummarizationMCoNaLa: A Benchmark for Code Generation from Multiple Natural Languages
While there has been a recent burgeoning of applications at the intersection of natural and programming languages, such as code generation and code summarization, these applications are usually English-centric. This crea…
Code GenerationCode SummarizationWhat Do They Capture? -- A Structural Analysis of Pre-Trained Language Models for Source Code
Recently, many pre-trained language models for source code have been proposed to model the context of code and serve as a basis for downstream code intelligence tasks such as code completion, code search, and code summar…
Code CompletionCode SearchCode SummarizationSource Code Summarization with Structural Relative Position Guided Transformer
Source code summarization aims at generating concise and clear natural language descriptions for programming languages. Well-written code summaries are beneficial for programmers to participate in the software developmen…
Code SummarizationPositionSource Code SummarizationCompositionality-Aware Graph2Seq Learning
Graphs are a highly expressive data structure, but it is often difficult for humans to find patterns from a complex graph. Hence, generating human-interpretable sequences from graphs have gained interest, called graph2se…
Code SummarizationSource Code SummarizationMeta Learning for Code Summarization
Source code summarization is the task of generating a high-level natural language description for a segment of programming language code. Current neural models for the task differ in their architecture and the aspects of…
Code SummarizationMeta-LearningSource Code SummarizationCode Summarization: Do Transformers Really Understand Code?
Recent approaches for automatic code summarization rely on fine-tuned transformer based language Models often injected with program analysis information. We perform empirical studies to analyze the extent to which these …
Code SummarizationSummarize and Generate to Back-translate: Unsupervised Translation of Programming Languages
Back-translation is widely known for its effectiveness for neural machine translation when little to no parallel data is available. In this approach, a source-to-target model is coupled with a target-to-source model and …
Code GenerationCode SummarizationMachine TranslationTranslationAssemble Foundation Models for Automatic Code Summarization
Automatic code summarization is beneficial to daily software development since it could help reduce the requirement of manual writing. Currently, artificial intelligence is undergoing a paradigm shift. The foundation mod…
Code Documentation GenerationCode SummarizationSequence-to-sequence Language ModelingSource Code Summarization+1Multilingual training for Software Engineering
Well-trained machine-learning models, which leverage large amounts of open-source software data, have now become an interesting approach to automating many software engineering tasks. Several SE tasks have all been subje…
Code SummarizationRetrievalType predictionAST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization
Code summarization aims to generate brief natural language descriptions for source code. As source code is highly structured and follows strict programming language grammars, its Abstract Syntax Tree (AST) is often lever…
Code SummarizationIntegrating Tree Path in Transformer for Code Representation
Learning distributed representation of source code requires modelling its syntax and semantics. Recent state-of-the-art models leverage highly structured source code representations, such as the syntax trees and paths th…
Code SummarizationGraph Conditioned Sparse-Attention for Improved Source Code Understanding
Transformer architectures have been successfully used in learning source code representations. The fusion between a graph representation like Abstract Syntax Tree (AST) and a source code sequence makes the use of current…
Code SummarizationVariable misuseLeveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflow
Automated source code summarization is a task that generates summarized information about the purpose, usage, and--or implementation of methods and classes to support understanding of these code entities. Multiple approa…
Code SummarizationSource Code SummarizationGN-Transformer: Fusing Sequence and Graph Representation for Improved Code Summarization
As opposed to natural languages, source code understanding is influenced by grammatical relationships between tokens regardless of their identifier name. Graph representations of source code such as Abstract Syntax Tree …
Code SummarizationCan Neural Networks Understand Programs like Humans?
Program understanding is a fundamental task in program language processing. Despite the success, existing works fail to take human minds as reference in understanding programs. In this paper, we incorporate human minds a…
Clone DetectionCode SummarizationGraph Neural NetworkRetrieval-based Layer-wise Adaptive Transformer for Source Code Summarization
We propose a model that learns both the sequential and the structural features of code for source code summarization. We adopt the Abstract Syntax Tree (AST) and graph convolution to model the structural information and …
Code SummarizationRetrievalSource Code SummarizationMeta Learning for Code Summarization
Source code summarization is the task of generating a high-level natural language description for a segment of programming language code. Current neural models for the task differ in their architecture and the aspects of…
Code SummarizationMeta-LearningSource Code Summarization