Papers Program Repair
“Program Repair” 태그가 달린 논문 192편 · 필터 해제
Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning
Binary code analysis is the foundation of crucial tasks in the security domain; thus building effective binary analysis techniques is more important than ever. Large language models (LLMs) although have brought impressiv…
Code GenerationCode TranslationCompiler OptimizationContrastive Learning+2ConDefects: A New Dataset to Address the Data Leakage Concern for LLM-based Fault Localization and Program Repair
With the growing interest on Large Language Models (LLMs) for fault localization and program repair, ensuring the integrity and generalizability of the LLM-based methods becomes paramount. The code in existing widely-ado…
BenchmarkingFault localizationProgram RepairEnhancing Genetic Improvement Mutations Using Large Language Models
Large language models (LLMs) have been successfully applied to software engineering tasks, including program repair. However, their application in search-based techniques such as Genetic Improvement (GI) is still largely…
Program RepairAutomated Bug Generation in the era of Large Language Models
Bugs are essential in software engineering; many research studies in the past decades have been proposed to detect, localize, and repair bugs in software systems. Effectiveness evaluation of such techniques requires comp…
Program RepairProgram Repair with Minimal Edits Using CodeT5
Programmers often struggle to identify and fix bugs in their programs. In recent years, many language models (LMs) have been proposed to fix erroneous programs and support error recovery. However, the LMs tend to generat…
Program RepairFrustrated with Code Quality Issues? LLMs can Help!
As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis tools are used in developer workflows to f…
Instruction FollowingProgram RepairRAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair
Automatic program repair (APR) is crucial to reduce manual debugging efforts for developers and improve software reliability. While conventional search-based techniques typically rely on heuristic rules or a redundancy a…
Language ModellingProgram RepairRetrievalCopiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair
During Automated Program Repair (APR), it can be challenging to synthesize correct patches for real-world systems in general-purpose programming languages. Recent Large Language Models (LLMs) have been shown to be helpfu…
Code GenerationProgram RepairvalidGraph Neural Networks For Mapping Variables Between Programs -- Extended Version
Automated program analysis is a pivotal research domain in many areas of Computer Science -- Formal Methods and Artificial Intelligence, in particular. Due to the undecidability of the problem of program equivalence, com…
Clone DetectionProgram RepairAn Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code
Large language models trained on source code can support a variety of software development tasks, such as code recommendation and program repair. Large amounts of data for training such models benefit the models' perform…
Program RepairBetter patching using LLM prompting, via Self-Consistency
Large Language models (LLMs) can be induced to solve non-trivial problems with "few-shot" prompts including illustrative problem-solution examples. Now if the few-shots also include "chain of thought" (CoT) explanations,…
Program RepairHow Effective Are Neural Networks for Fixing Security Vulnerabilities
Security vulnerability repair is a difficult task that is in dire need of automation. Two groups of techniques have shown promise: (1) large code language models (LLMs) that have been pre-trained on source code for tasks…
Code CompletionProgram RepairIs ChatGPT the Ultimate Programming Assistant -- How far is it?
Recently, the ChatGPT LLM has received great attention: it can be used as a bot for discussing source code, prompting it to suggest changes, provide descriptions or even generate code. Typical demonstrations generally fo…
Code GenerationCode SummarizationProgram RepairPrompt EngineeringFully Autonomous Programming with Large Language Models
Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answer (as measured by text similarity metri…
Program RepairProgram Synthesistext similarityEnhancing Automated Program Repair through Fine-tuning and Prompt Engineering
Sequence-to-sequence models have been used to transform erroneous programs into correct ones when trained with a large enough dataset. Some recent studies also demonstrated strong empirical evidence that code review coul…
Program RepairPrompt EngineeringTeaching Large Language Models to Self-Debug
Large language models (LLMs) have achieved impressive performance on code generation. However, for complex programming tasks, generating the correct solution in one go becomes challenging, thus some prior works have desi…
Code GenerationLanguage ModelingLanguage ModellingLarge Language Model+4RunBugRun -- An Executable Dataset for Automated Program Repair
Recently, we can notice a transition to data-driven techniques in Automated Program Repair (APR), in particular towards deep neural networks. This entails training on hundreds of thousands or even millions of non-executa…
Program RepairKeep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT
Automated Program Repair (APR) aims to automatically generate patches for buggy programs. Recent APR work has been focused on leveraging modern Large Language Models (LLMs) to directly generate patches for APR. Such LLM-…
Program RepairRevisiting the Plastic Surgery Hypothesis via Large Language Models
Automated Program Repair (APR) aspires to automatically generate patches for an input buggy program. Traditional APR tools typically focus on specific bug types and fixes through the use of templates, heuristics, and for…
Program RepairxCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval
Recently, pre-trained large language models (LLMs) have shown impressive abilities in generating codes from natural language descriptions, repairing buggy codes, translating codes between languages, and retrieving releva…
Program RepairProgram SynthesisRetrieval