The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models
Fuente:
arXiv
Saved in:
| Main Authors: | Ruiz, Fernando Vallecillos, Hort, Max, Moonen, Leon |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Wisdom and Delusion of LLM Ensembles for Code Generation and Repair
by: Vallecillos-Ruiz, Fernando, et al.
Published: (2025)
by: Vallecillos-Ruiz, Fernando, et al.
Published: (2025)
Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation
by: Ruiz, Fernando Vallecillos, et al.
Published: (2024)
by: Ruiz, Fernando Vallecillos, et al.
Published: (2024)
The Impact of Fine-tuning Large Language Models on Automated Program Repair
by: Macháček, Roman, et al.
Published: (2025)
by: Macháček, Roman, et al.
Published: (2025)
Codehacks: A Dataset of Adversarial Tests for Competitive Programming Problems Obtained from Codeforces
by: Hort, Max, et al.
Published: (2025)
by: Hort, Max, et al.
Published: (2025)
Semantic-Preserving Transformations as Mutation Operators: A Study on Their Effectiveness in Defect Detection
by: Hort, Max, et al.
Published: (2025)
by: Hort, Max, et al.
Published: (2025)
A Comparative Study on Large Language Models for Log Parsing
by: Astekin, Merve, et al.
Published: (2024)
by: Astekin, Merve, et al.
Published: (2024)
Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Models
by: Grishina, Anastasiia, et al.
Published: (2025)
by: Grishina, Anastasiia, et al.
Published: (2025)
AuPair: Golden Example Pairs for Code Repair
by: Mavalankar, Aditi, et al.
Published: (2025)
by: Mavalankar, Aditi, et al.
Published: (2025)
Learner-Tailored Program Repair: A Solution Generator with Iterative Edit-Driven Retrieval Enhancement
by: Dai, Zhenlong, et al.
Published: (2026)
by: Dai, Zhenlong, et al.
Published: (2026)
AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs?
by: Press, Ori, et al.
Published: (2025)
by: Press, Ori, et al.
Published: (2025)
XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts
by: Ding, Yifeng, et al.
Published: (2024)
by: Ding, Yifeng, et al.
Published: (2024)
Benchmarking Educational Program Repair
by: Koutcheme, Charles, et al.
Published: (2024)
by: Koutcheme, Charles, et al.
Published: (2024)
How Do Your Code LLMs Perform? Empowering Code Instruction Tuning with High-Quality Data
by: Wang, Yejie, et al.
Published: (2024)
by: Wang, Yejie, et al.
Published: (2024)
Aligning the Objective of LLM-based Program Repair
by: Xu, Junjielong, et al.
Published: (2024)
by: Xu, Junjielong, et al.
Published: (2024)
Solution-oriented Agent-based Models Generation with Verifier-assisted Iterative In-context Learning
by: Niu, Tong, et al.
Published: (2024)
by: Niu, Tong, et al.
Published: (2024)
MemRepair: Hierarchical Memory for Agentic Repository-Level Vulnerability Repair
by: Liu, Simiao, et al.
Published: (2026)
by: Liu, Simiao, et al.
Published: (2026)
DDPT: Diffusion-Driven Prompt Tuning for Large Language Model Code Generation
by: Li, Jinyang, et al.
Published: (2025)
by: Li, Jinyang, et al.
Published: (2025)
MCP-Solver: Integrating Language Models with Constraint Programming Systems
by: Szeider, Stefan
Published: (2024)
by: Szeider, Stefan
Published: (2024)
LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation
by: Ma, Zeyuan, et al.
Published: (2024)
by: Ma, Zeyuan, et al.
Published: (2024)
Predicting Intermittent Job Failure Categories for Diagnosis Using Few-Shot Fine-Tuned Language Models
by: Aïdasso, Henri, et al.
Published: (2026)
by: Aïdasso, Henri, et al.
Published: (2026)
ADReFT: Adaptive Decision Repair for Safe Autonomous Driving via Reinforcement Fine-Tuning
by: Cheng, Mingfei, et al.
Published: (2025)
by: Cheng, Mingfei, et al.
Published: (2025)
$\textbf{Only-IF}$:Revealing the Decisive Effect of Instruction Diversity on Generalization
by: Zhang, Dylan, et al.
Published: (2024)
by: Zhang, Dylan, et al.
Published: (2024)
Step Rejection Fine-Tuning: A Practical Distillation Recipe
by: Slinko, Igor, et al.
Published: (2026)
by: Slinko, Igor, et al.
Published: (2026)
CP-Agent: Agentic Constraint Programming
by: Szeider, Stefan
Published: (2025)
by: Szeider, Stefan
Published: (2025)
GRAPH-GRPO-LEX: Contract Graph Modeling and Reinforcement Learning with Group Relative Policy Optimization
by: Dechtiar, Moriya, et al.
Published: (2025)
by: Dechtiar, Moriya, et al.
Published: (2025)
Do LLMs Consider Security? An Empirical Study on Responses to Programming Questions
by: Sajadi, Amirali, et al.
Published: (2025)
by: Sajadi, Amirali, et al.
Published: (2025)
Combinatorial Optimization for All: Using LLMs to Aid Non-Experts in Improving Optimization Algorithms
by: Sartori, Camilo Chacón, et al.
Published: (2025)
by: Sartori, Camilo Chacón, et al.
Published: (2025)
A Semantic-based Optimization Approach for Repairing LLMs: Case Study on Code Generation
by: Gu, Jian, et al.
Published: (2025)
by: Gu, Jian, et al.
Published: (2025)
IRepair: An Intent-Aware Approach to Repair Data-Driven Errors in Large Language Models
by: Imtiaz, Sayem Mohammad, et al.
Published: (2025)
by: Imtiaz, Sayem Mohammad, et al.
Published: (2025)
Exploring Large Language Models in Resolving Environment-Related Crash Bugs: Localizing and Repairing
by: Du, Xueying, et al.
Published: (2023)
by: Du, Xueying, et al.
Published: (2023)
LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?
by: Zheng, Zihan, et al.
Published: (2025)
by: Zheng, Zihan, et al.
Published: (2025)
NeuFair: Neural Network Fairness Repair with Dropout
by: Dasu, Vishnu Asutosh, et al.
Published: (2024)
by: Dasu, Vishnu Asutosh, et al.
Published: (2024)
Is Programming by Example solved by LLMs?
by: Li, Wen-Ding, et al.
Published: (2024)
by: Li, Wen-Ding, et al.
Published: (2024)
EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking
by: Wei, Anjiang, et al.
Published: (2025)
by: Wei, Anjiang, et al.
Published: (2025)
Utilizing Deep Learning to Optimize Software Development Processes
by: Li, Keqin, et al.
Published: (2024)
by: Li, Keqin, et al.
Published: (2024)
GSO: Challenging Software Optimization Tasks for Evaluating SWE-Agents
by: Shetty, Manish, et al.
Published: (2025)
by: Shetty, Manish, et al.
Published: (2025)
Maestro: Joint Graph & Config Optimization for Reliable AI Agents
by: Wang, Wenxiao, et al.
Published: (2025)
by: Wang, Wenxiao, et al.
Published: (2025)
RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
by: Silva, André, et al.
Published: (2023)
by: Silva, André, et al.
Published: (2023)
ReGAL: Refactoring Programs to Discover Generalizable Abstractions
by: Stengel-Eskin, Elias, et al.
Published: (2024)
by: Stengel-Eskin, Elias, et al.
Published: (2024)
A Systematic Approach to Predict the Impact of Cybersecurity Vulnerabilities Using LLMs
by: Høst, Anders Mølmen, et al.
Published: (2025)
by: Høst, Anders Mølmen, et al.
Published: (2025)
Similar Items
-
Wisdom and Delusion of LLM Ensembles for Code Generation and Repair
by: Vallecillos-Ruiz, Fernando, et al.
Published: (2025) -
Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation
by: Ruiz, Fernando Vallecillos, et al.
Published: (2024) -
The Impact of Fine-tuning Large Language Models on Automated Program Repair
by: Macháček, Roman, et al.
Published: (2025) -
Codehacks: A Dataset of Adversarial Tests for Competitive Programming Problems Obtained from Codeforces
by: Hort, Max, et al.
Published: (2025) -
Semantic-Preserving Transformations as Mutation Operators: A Study on Their Effectiveness in Defect Detection
by: Hort, Max, et al.
Published: (2025)