SOTAVerified

Program Repair

Task of teaching ML models to modify an existing program to fix a bug in a given code.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 132 papers

TitleStatusHype
Automated Bug Generation in the era of Large Language Models—0
The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models—0
Learning to Fix Build Errors with Graph2Diff Neural Networks—0
The Impact of Input Order Bias on Large Language Models for Software Fault Localization—0
LessLeak-Bench: A First Investigation of Data Leakage in LLMs Across 83 Software Engineering Benchmarks—0
Leveraging Causal Inference for Explainable Automatic Program Repair—0
Better patching using LLM prompting, via Self-Consistency—0
Mapping the Structure and Evolution of Software Testing Research Over the Past Three Decades—0
MdEval: Massively Multilingual Code Debugging—0
MergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair—0
MultiFix: Learning to Repair Multiple Errors by Optimal Alignment Learning—0
NARRepair: Non-Autoregressive Code Generation Model for Automatic Program Repair—0
Attention Pruning: Automated Fairness Repair of Language Models via Surrogate Simulated Annealing—0
Neural Program Repair: Systems, Challenges and Solutions—0
NExT: Teaching Large Language Models to Reason about Code Execution—0
Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning—0
A Study of Vulnerability Repair in JavaScript Programs with Large Language Models—0
Obstacles in Fully Automatic Program Repair: A survey—0
Towards Effectively Leveraging Execution Traces for Program Repair with Code LLMs—0
Towards Mixed Optimization for Reinforcement Learning with Program Synthesis—0
Peer-aided Repairer: Empowering Large Language Models to Repair Advanced Student Assignments—0
An LLM-as-Judge Metric for Bridging the Gap with Human Evaluation in SE Tasks—0
Understanding Software Engineering Agents: A Study of Thought-Action-Result Trajectories—0
Program Repair with Minimal Edits Using CodeT5—0
Program Repair with Repeated Learning—0
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All datasetsDeepFixGitHub-PythonHumanEvalPackTFix's Code Patches Data

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DrRepair + BIFIAverage Success Rate71.7—Unverified
2DrRepairAverage Success Rate68.2—Unverified
3SampleFixAverage Success Rate45.3—Unverified
4RLAssistAverage Success Rate26.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Transformer + BIFIAccuracy (%)90.5—Unverified
2TransformerAccuracy (%)62—Unverified
#ModelMetricClaimedVerifiedStatus
1MGDebugger (DeepSeek-Coder-V2-Lite)Pass@197.6—Unverified
#ModelMetricClaimedVerifiedStatus
1TFixError Removal678—Unverified