Papers Code Summarization
“Code Summarization” 태그가 달린 논문 163편 · 필터 해제
Genetic Auto-prompt Learning for Pre-trained Code Intelligence Language Models
As Pre-trained Language Models (PLMs), a popular approach for code intelligence, continue to grow in size, the computational cost of their usage has become prohibitively expensive. Prompt learning, a recent development i…
Code SummarizationCode TranslationPrompt LearningEmpirical Studies of Parameter Efficient Methods for Large Language Models of Code and Knowledge Transfer to R
Parameter Efficient Fine-Tuning (PEFT) methods are proposed as an alternative fine-tuning approach for Large Language Models (LLM) to minimize high training costs. While prior research demonstrates the effectiveness of P…
Code Summarizationparameter-efficient fine-tuningTransfer LearningRead between the lines -- Functionality Extraction From READMEs
While text summarization is a well-known NLP task, in this paper, we introduce a novel and useful variant of it called functionality extraction from Git README files. Though this task is a text2text generation at an abst…
Code Summarizationtext2text-generationText2text GenerationText SummarizationDo Machines and Humans Focus on Similar Code? Exploring Explainability of Large Language Models in Code Summarization
Recent language models have demonstrated proficiency in summarizing source code. However, as in many other domains of machine learning, language models of code lack sufficient explainability. Informally, we lack a formul…
Code SummarizationLanguage ModellingEyeTrans: Merging Human and Machine Attention for Neural Code Summarization
Neural code summarization leverages deep learning models to automatically generate brief natural language summaries of code snippets. The development of Transformer models has led to extensive use of attention during mod…
Code SummarizationStudying Vulnerable Code Entities in R
Pre-trained Code Language Models (Code-PLMs) have shown many advancements and achieved state-of-the-art results for many software engineering tasks in the past few years. These models are mainly targeted for popular prog…
Code SummarizationMethod name predictionA Prompt Learning Framework for Source Code Summarization
(Source) code summarization is the task of automatically generating natural language summaries (also called comments) for given code snippets. Recently, with the successful application of large language models (LLMs) in …
Code SummarizationFew-Shot Learningparameter-efficient fine-tuningPrompt Learning+2Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models
Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature. This study delves into the potential of large language models (LLMs) for binary code compreh…
BenchmarkingCode SummarizationGPUSemantic Similarity+1Breaking the Silence: the Threats of Using LLMs in Software Engineering
Large Language Models (LLMs) have gained considerable traction within the Software Engineering (SE) community, impacting various SE tasks from code completion to test generation, from program repair to code summarization…
Code CompletionCode SummarizationLanguage ModelingLanguage Modelling+1Transfer Attacks and Defenses for Large Language Models on Coding Tasks
Modern large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities for coding tasks including writing and reasoning about code. They improve upon previous neural network models of code, such …
Code SummarizationDocGen: Generating Detailed Parameter Docstrings in Python
Documentation debt hinders the effective utilization of open-source software. Although code summarization tools have been helpful for developers, most would prefer a detailed account of each parameter in a function rathe…
Code SummarizationUnderstanding Code Semantics: An Evaluation of Transformer Models in Summarization
This paper delves into the intricacies of code summarization using advanced transformer-based language models. Through empirical studies, we evaluate the efficacy of code summarization by altering function and variable n…
Code SummarizationExploring Large Language Models for Code Explanation
Automating code documentation through explanatory text can prove highly beneficial in code understanding. Large Language Models (LLMs) have made remarkable strides in Natural Language Processing, especially within softwa…
Code GenerationCode SummarizationCP-BCS: Binary Code Summarization Guided by Control Flow Graph and Pseudo Code
Automatically generating function summaries for binaries is an extremely valuable but challenging task, since it involves translating the execution behavior and semantics of the low-level language (assembly code) into hu…
Code SummarizationLeveraging Deep Learning for Abstractive Code Summarization of Unofficial Documentation
Usually, programming languages have official documentation to guide developers with APIs, methods, and classes. However, researchers identified insufficient or inadequate documentation examples and flaws with the API's c…
Code SummarizationDeep LearningText SummarizationBeyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain
Code Large Language Models (Code LLMs) are being increasingly employed in real-life applications, so evaluating them is critical. While the conventional accuracy evaluates the performance of Code LLMs on a set of individ…
Code GenerationCode SummarizationAn Assessment of ChatGPT on Log Data
Recent development of large language models (LLMs), such as ChatGPT has been widely applied to a wide range of software engineering tasks. Many papers have reported their analysis on the potential advantages and limitati…
Code SummarizationText GenerationRevisiting File Context for Source Code Summarization
Source code summarization is the task of writing natural language descriptions of source code. A typical use case is generating short summaries of subroutines for use in API documentation. The heart of almost all current…
Code SummarizationDecoderSource Code SummarizationLaminar: A New Serverless Stream-based Framework with Semantic Code Search and Code Completion
This paper introduces Laminar, a novel serverless framework based on dispel4py, a parallel stream-based dataflow library. Laminar efficiently manages streaming workflows and components through a dedicated registry, offer…
Code CompletionCode SearchCode SummarizationDistilled GPT for Source Code Summarization
A code summary is a brief natural language description of source code. Summaries are usually only a single sentence long, and yet form the backbone of developer documentation. A short descriptions such as "changes all vi…
Code SummarizationGPUKnowledge DistillationSentence+1