Papers Program Repair
“Program Repair” 태그가 달린 논문 192편 · 필터 해제
CORE: Benchmarking LLMs Code Reasoning Capabilities through Static Analysis Tasks
Large language models (LLMs) have been widely adopted across diverse software engineering domains, such as code generation, program repair, and vulnerability detection. These applications require understanding beyond sur…
BenchmarkingCode GenerationProgram RepairVulnerability Detection$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models
Automatic Program Repair (APR) is a core technology in software development and maintenance, with aims to enable automated defect repair with minimal human intervention. In recent years, the substantial advancements in L…
Program RepairUnderstanding Software Engineering Agents: A Study of Thought-Action-Result Trajectories
Large Language Model (LLM)-based agents are increasingly employed to automate complex software engineering tasks such as program repair and issue resolution. These agents operate by autonomously generating natural langua…
Large Language ModelProgram RepairDissecting the SWE-Bench Leaderboards: Profiling Submitters and Architectures of LLM- and Agent-Based Repair Systems
The rapid progress in Automated Program Repair (APR) has been driven by advances in AI, particularly large language models (LLMs) and agent-based systems. SWE-Bench is a recent benchmark designed to evaluate LLM-based re…
Program RepairSemAgent: A Semantics Aware Program Repair Agent
Large Language Models (LLMs) have shown impressive capabilities in downstream software engineering tasks such as Automated Program Repair (APR). In particular, there has been a lot of research on repository-level issue-r…
Program RepairA Multi-Dataset Evaluation of Models for Automated Vulnerability Repair
Software vulnerabilities pose significant security threats, requiring effective mitigation. While Automated Program Repair (APR) has advanced in fixing general bugs, vulnerability patching, a security-critical aspect of …
Program RepairVulnerability DetectionAn LLM-as-Judge Metric for Bridging the Gap with Human Evaluation in SE Tasks
Large Language Models (LLMs) and other automated techniques have been increasingly used to support software developers by generating software artifacts such as code snippets, patches, and comments. However, accurately as…
Code GenerationCode SummarizationHumanEvalProgram RepairGradient-Based Program Repair: Fixing Bugs in Continuous Program Spaces
Automatic program repair seeks to generate correct code from buggy programs, with most approaches searching the correct program in a discrete, symbolic space of source code tokens. This symbolic search is fundamentally l…
Program RepairSynthetic Code Surgery: Repairing Bugs and Vulnerabilities with LLMs and Synthetic Data
This paper presents a novel methodology for enhancing Automated Program Repair (APR) through synthetic data generation utilizing Large Language Models (LLMs). Current APR systems are constrained by the limited availabili…
Program RepairSynthetic Data GenerationTowards Effectively Leveraging Execution Traces for Program Repair with Code LLMs
Large Language Models (LLMs) show promising performance on various programming tasks, including Automatic Program Repair (APR). However, most approaches to LLM-based APR are limited to the static analysis of the programs…
Program RepairThe Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models
Automatic program repair (APR) aims to reduce the manual efforts required to identify and fix errors in source code. Before the rise of LLM-based agents, a common strategy was to increase the number of generated patches,…
HumanEvalProgram RepairSWE-Synth: Synthesizing Verifiable Bug-Fix Data to Enable Large Language Models in Resolving Real-World Bugs
Large language models (LLMs) are transforming automated program repair (APR) through agent-based approaches that localize bugs, generate patches, and verify fixes. However, the lack of high-quality, scalable training dat…
Program RepairUsing ML filters to help automated vulnerability repairs: when it helps and when it doesn't
[Context:] The acceptance of candidate patches in automated program repair has been typically based on testing oracles. Testing requires typically a costly process of building the application while ML models can be used …
Program RepairVulnerability DetectionCoSIL: Software Issue Localization via LLM-Driven Code Repository Graph Searching
Large language models (LLMs) have significantly advanced autonomous software engineering, leading to a growing number of software engineering agents that assist developers in automatic program repair. Issue localization …
Program RepairAttention Pruning: Automated Fairness Repair of Language Models via Surrogate Simulated Annealing
This paper explores pruning attention heads as a post-processing bias mitigation method for large language models (LLMs). Modern AI systems such as LLMs are expanding into sensitive social contexts where fairness concern…
FairnessProgram RepairEvaluating the Generalizability of LLMs in Automated Program Repair
LLM-based automated program repair methods have attracted significant attention for their state-of-the-art performance. However, they were primarily evaluated on a few well known datasets like Defects4J, raising question…
Program RepairPrompt EngineeringLess is More: Adaptive Program Repair with Bug Localization and Preference Learning
Automated Program Repair (APR) is a task to automatically generate patches for the buggy code. However, most research focuses on generating correct patches while ignoring the consistency between the fixed code and the or…
Bug fixingProgram RepairWhere's the Bug? Attention Probing for Scalable Fault Localization
Ensuring code correctness remains a challenging problem even as large language models (LLMs) become increasingly capable at code-related tasks. While LLM-based program repair systems can propose bug fixes using only a us…
Fault localizationProgram RepairLessLeak-Bench: A First Investigation of Data Leakage in LLMs Across 83 Software Engineering Benchmarks
Large Language Models (LLMs) are widely utilized in software engineering (SE) tasks, such as code generation and automated program repair. However, their reliance on extensive and often undisclosed pre-training datasets …
Code GenerationProgram RepairAgentic Bug Reproduction for Effective Automated Program Repair at Google
Bug reports often lack sufficient detail for developers to reproduce and fix the underlying defects. Bug Reproduction Tests (BRTs), tests that fail when the bug is present and pass when it has been resolved, are crucial …
Large Language ModelProgram Repair