Papers with Code 아카이브
Program Repair
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
- 8
Task of teaching ML models to modify an existing program to fix a bug in a given code.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models
Understanding Software Engineering Agents: A Study of Thought-Action-Result Trajectories
Dissecting the SWE-Bench Leaderboards: Profiling Submitters and Architectures of LLM- and Agent-Based Repair Systems
SemAgent: A Semantics Aware Program Repair Agent
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair
An LLM-as-Judge Metric for Bridging the Gap with Human Evaluation in SE Tasks
Benchmarking and Enhancing LLM Agents in Localizing Linux Kernel Bugs
Gradient-Based Program Repair: Fixing Bugs in Continuous Program Spaces
Data Mining-Based Techniques for Software Fault Localization
Synthetic Code Surgery: Repairing Bugs and Vulnerabilities with LLMs and Synthetic Data
Towards Effectively Leveraging Execution Traces for Program Repair with Code LLMs
The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models
SWE-Synth: Synthesizing Verifiable Bug-Fix Data to Enable Large Language Models in Resolving Real-World Bugs
Using ML filters to help automated vulnerability repairs: when it helps and when it doesn't
How Accurately Do Large Language Models Understand Code?
Thinking Longer, Not Larger: Enhancing Software Engineering Agents via Scaling Test-Time Compute
CoSIL: Software Issue Localization via LLM-Driven Code Repository Graph Searching
Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study)
Attention Pruning: Automated Fairness Repair of Language Models via Surrogate Simulated Annealing
Evaluating the Generalizability of LLMs in Automated Program Repair
Less is More: Adaptive Program Repair with Bug Localization and Preference Learning
Fault Localization and State Estimation of Power Grid under Parallel Cyber-Physical Attacks
Where's the Bug? Attention Probing for Scalable Fault Localization
LessLeak-Bench: A First Investigation of Data Leakage in LLMs Across 83 Software Engineering Benchmarks
Agentic Bug Reproduction for Effective Automated Program Repair at Google
o3-mini vs DeepSeek-R1: Which One is Safer?
Fault Localization via Fine-tuning Large Language Models with Mutation Generated Stack Traces
Evaluating Agent-based Program Repair at Google
AIOpsLab: A Holistic Framework to Evaluate AI Agents for Enabling Autonomous Clouds
The Impact of Input Order Bias on Large Language Models for Software Fault Localization
Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization
Integrating Various Software Artifacts for Better LLM-based Bug Localization and Program Repair
AEGIS: An Agent-based Framework for General Bug Reproduction from Issue Descriptions
The Power of Types: Exploring the Impact of Type Checking on Neural Bug Detection in Dynamically Typed Languages
Planning-Driven Programming: A Large Language Model Programming Workflow
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.