Papers Program Repair
“Program Repair” 태그가 달린 논문 192편 · 필터 해제
o3-mini vs DeepSeek-R1: Which One is Safer?
The irruption of DeepSeek-R1 constitutes a turning point for the AI industry in general and the LLMs in particular. Its capabilities have demonstrated outstanding performance in several tasks, including creative thinking…
Code GenerationProgram RepairQuestion AnsweringEvaluating Agent-based Program Repair at Google
Agent-based program repair offers to automatically resolve complex bugs end-to-end by combining the planning, tool use, and code generation abilities of modern LLMs. Recent work has explored the use of agent-based repair…
Code GenerationProgram RepairThe Impact of Input Order Bias on Large Language Models for Software Fault Localization
Large Language Models (LLMs) have shown significant potential in software engineering tasks such as Fault Localization (FL) and Automatic Program Repair (APR). This study investigates how input order and context size inf…
Fault localizationMemorizationProgram RepairCounterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization
Automated Program Repair (APR) for introductory programming assignments (IPAs) is motivated by the large number of student enrollments in programming courses each year. Since providing feedback on IPAs requires substanti…
Fault localizationProgram RepairZero-Shot LearningIntegrating Various Software Artifacts for Better LLM-based Bug Localization and Program Repair
LLMs have garnered considerable attention for their potential to streamline Automated Program Repair (APR). LLM-based approaches can either insert the correct code or directly generate patches when provided with buggy me…
Fault localizationProgram RepairPlanning-Driven Programming: A Large Language Model Programming Workflow
The strong performance of large language models (LLMs) raises extensive discussion on their application to code generation. Recent research suggests continuous program refinements through visible tests to improve code ge…
Code GenerationHumanEvalLanguage ModelingLanguage Modelling+4A Comprehensive Survey of AI-Driven Advancements and Techniques in Automated Program Repair and Code Generation
Bug fixing and code generation have been core research topics in software development for many years. The recent explosive growth in Large Language Models has completely transformed these spaces, putting in reach incredi…
Bug fixingCode GenerationProgram RepairSurveyMdEval: Massively Multilingual Code Debugging
Code large language models (LLMs) have made significant progress in code debugging by directly generating the correct code based on the buggy code snippet. Programming benchmarks, typically consisting of buggy code snipp…
Program RepairSemantic-guided Search for Efficient Program Repair with Large Language Models
In this paper, we first show that increases in beam size of even just small-sized LLM (1B-7B parameters) require an extensive GPU resource consumption, leading to up to 80% of recurring crashes due to memory overloads in…
GPUHumanEvalProgram RepairCollu-Bench: A Benchmark for Predicting Language Model Hallucinations in Code
Despite their success, large language models (LLMs) face the critical challenge of hallucinations, generating plausible but incorrect content. While much research has focused on hallucinations in multiple modalities incl…
Code GenerationHallucinationLanguage ModelingLanguage Modelling+1In-Context Code-Text Learning for Bimodal Software Engineering
Bimodal software analysis initially appeared to be within reach with the advent of large language models. Unfortunately, the complex interplay of natural language text and code in software engineering, presents unique ch…
Clone DetectionIn-Context LearningProgram RepairPrompt Learning+1Exploring the Potential of Conversational Test Suite Based Program Repair on SWE-bench
Automatic program repair at project level may open yet to be seen opportunities in various fields of human activity. Since the SWE-Bench challenge was presented, we have seen numerous of solutions. Patch generation is a …
Program RepairvalidFrom Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
While large language models have made significant strides in code generation, the pass rate of the generated code is bottlenecked on subtle errors, often requiring human intervention to pass tests, especially for complex…
Auto DebuggingBug fixingCode GenerationHumanEval+1RepairBench: Leaderboard of Frontier Models for Program Repair
AI-driven program repair uses AI models to repair buggy software by producing patches. Rapid advancements in AI surely impact state-of-the-art performance of program repair. Yet, grasping this progress requires frequent …
Program RepairCan GPT-O1 Kill All Bugs? An Evaluation of GPT-Family LLMs on QuixBugs
LLMs have long demonstrated remarkable effectiveness in automatic program repair (APR), with OpenAI's ChatGPT being one of the most widely used models in this domain. Through continuous iterations and upgrades of GPT-fam…
AllProgram RepairHyperAgent: Generalist Software Engineering Agents to Solve Coding Tasks at Scale
Large Language Models (LLMs) have revolutionized software engineering (SE), showcasing remarkable proficiency in various coding tasks. Despite recent advancements that have enabled the creation of autonomous software age…
Code GenerationFault localizationGitHub issue resolutionProgram RepairEnhancing Automated Program Repair with Solution Design
Automatic Program Repair (APR) endeavors to autonomously rectify issues within specific projects, which generally encompasses three categories of tasks: bug resolution, new feature development, and feature enhancement. D…
Program RepairRePair: Automated Program Repair with Process-based Feedback
The gap between the trepidation of program reliability and the expense of repairs underscores the indispensability of Automated Program Repair (APR). APR is instrumental in transforming vulnerable programs into more robu…
Program RepairMergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair
Large Language Models (LLMs) have shown high capabilities in several software development-related tasks such as program repair, documentation, code refactoring, debugging, and testing. However, training these models requ…
parameter-efficient fine-tuningProgram RepairSpecRover: Code Intent Extraction via LLMs
Autonomous program improvement typically involves automatically producing bug fixes and feature additions. Such program improvement can be accomplished by a combination of large language model (LLM) and program analysis …
Code SearchLarge Language ModelProgram Repair