Papers Code Repair
“Code Repair” 태그가 달린 논문 70편 · 필터 해제
A Study on the Impact of Fault localization Granularity for Repository-Scale Code Repair Tasks
Automatic program repair can be a challenging task, especially when resolving complex issues at a repository-level, which often involves issue reproduction, fault localization, code repair, testing and validation. Issues…
Program RepairCode RepairResearchEnvBench: Benchmarking Agents on Environment Synthesis for Research Code Execution
Autonomous agents are increasingly expected to support scientific research, and recent benchmarks report progress in code repair and autonomous experimentation. However, these evaluations typically assume a pre-configure…
Code RepairProxyWar: Dynamic Assessment of LLM Code Generation in Game Arenas
Large language models (LLMs) have revolutionized automated code generation, yet the evaluation of their real-world effectiveness remains limited by static benchmarks and simplistic metrics. We present ProxyWar, a novel f…
Code GenerationCode RepairFeedback Loops and Code Perturbations in LLM-based Software Engineering: A Case Study on a C-to-Rust Translation System
The advent of strong generative AI has a considerable impact on various software engineering tasks such as code repair, test generation, or language translation. While tools like GitHub Copilot are already in widespread …
Code TranslationCode RepairAgentic Reinforcement Learning for Real-World Code Repair
We tackle the challenge of training reliable code-fixing agents in real repositories, where complex builds and shifting dependencies make evaluation unstable. We developed a verifiable pipeline with success defined as po…
Reinforcement LearningCode RepairSOCIA-Nabla: Textual Gradient Meets Multi-Agent Orchestration for Automated Simulator Generation
In this paper, we present SOCIA-Nabla, an end-to-end, agentic framework that treats simulator construction asinstance optimization over code within a textual computation graph. Specialized LLM-driven agents are embedded …
Code GenerationCode RepairAutomating Android Build Repair: Bridging the Reasoning-Execution Gap in LLM Agents with Domain-Specific Tools
Android is the largest mobile platform, yet automatically building applications remains a practical challenge. While Large Language Models (LLMs) show promise for code repair, their use for fixing Android build errors re…
Code RepairRepoDebug: Repository-Level Multi-Task and Multi-Language Debugging Evaluation of Large Language Models
Large Language Models (LLMs) have exhibited significant proficiency in code debugging, especially in automatic program repair, which may substantially reduce the time consumption of developers and enhance their efficienc…
Program RepairCode RepairReCode: Improving LLM-based Code Repair with Fine-Grained Retrieval-Augmented Generation
Recent advances in large language models (LLMs) have demonstrated impressive capabilities in code-related tasks, such as code generation and automated program repair. Despite their promising performance, most existing ap…
Code GenerationProgram RepairCode RepairBenchmark Dataset Generation and Evaluation for Excel Formula Repair with LLMs
Excel is a pervasive yet often complex tool, particularly for novice users, where runtime errors arising from logical mistakes or misinterpretations of functions pose a significant challenge. While large language models …
Code RepairDiffusion is a code repair operator and generator
Code diffusion models generate code by iteratively removing noise from the latent representation of a code snippet. During later steps of the diffusion process, when the code snippet has almost converged, differences bet…
Code RepairCodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks
Large Language Models (LLMs) have significantly advanced the state-of-the-art in various coding tasks. Beyond directly answering user queries, LLMs can also serve as judges, assessing and comparing the quality of respons…
BenchmarkingCode GenerationCode RepairAgent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving
As language agents tackle increasingly complex tasks, they struggle with effective error correction and experience reuse across domains. We introduce Agent KB, a hierarchical experience framework that enables complex age…
Code RepairTransfer LearningBreakpoint: Scalable evaluation of system-level reasoning in LLM code agents
Benchmarks for large language models (LLMs) have predominantly assessed short-horizon, localized reasoning. Existing long-horizon suites (e.g. SWE-bench) rely on manually curated issues, so expanding or tuning difficulty…
BenchmarkingCode RepairCrashFixer: A crash resolution agent for the Linux kernel
Code large language models (LLMs) have shown impressive capabilities on a multitude of software engineering tasks. In particular, they have demonstrated remarkable utility in the task of code repair. However, common benc…
Code RepairHow Accurately Do Large Language Models Understand Code?
Large Language Models (LLMs) are increasingly used in post-development tasks such as code repair and testing. A key factor in these tasks' success is the model's deep understanding of code. However, the extent to which L…
Code GenerationCode RepairFault localizationWhy Stop at One Error? Benchmarking LLMs as Data Science Code Debuggers for Multi-Hop and Multi-Bug Errors
LLMs are transforming software development, yet current code generation and code repair benchmarks mainly assess syntactic and functional correctness in simple, single-error cases. LLMs' capabilities to autonomously find…
BenchmarkingCode GenerationCode RepairRocketPPA: Code-Level Power, Performance, and Area Prediction via LLM and Mixture of Experts
This paper presents RocketPPA, a novel ultra-fast power, performance (delay), and area (PPA) estimator operating directly at the code-level abstraction using HDL code as input. The key technical innovation is its LLM-bas…
Code RepairFeature EngineeringLarge Language ModelMixture-of-Experts+1SolBench: A Dataset and Benchmark for Evaluating Functional Correctness in Solidity Code Completion and Repair
Smart contracts are crucial programs on blockchains, and their immutability post-deployment makes functional correctness vital. Despite progress in code completion models, benchmarks for Solidity, the primary smart contr…
Code CompletionCode RepairRetrievalAuPair: Golden Example Pairs for Code Repair
Scaling up inference-time compute has proven to be a valuable strategy in improving the performance of Large Language Models (LLMs) without fine-tuning. An important task that can benefit from additional inference-time c…
Code RepairIn-Context Learning