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
Teaching Large Language Models to Self-DebugCode0
RunBugRun -- An Executable Dataset for Automated Program Repair—0
Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT—0
Revisiting the Plastic Surgery Hypothesis via Large Language Models—0
xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and RetrievalCode1
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program RepairCode1
Conversational Automated Program Repair—0
Invalidator: Automated Patch Correctness Assessment via Semantic and Syntactic ReasoningCode0
Improving Automated Program Repair with Domain Adaptation—0
Detect-Localize-Repair: A Unified Framework for Learning to Debug with CodeT5—0
Repairing Bugs in Python Assignments Using Large Language Models—0
Repair Is Nearly Generation: Multilingual Program Repair with LLMs—0
BigIssue: A Realistic Bug Localization Benchmark—0
InvAASTCluster: On Applying Invariant-Based Program Clustering to Introductory Programming AssignmentsCode0
C-Pack of IPAs: A C90 Program Benchmark of Introductory Programming AssignmentsCode0
Leveraging Causal Inference for Explainable Automatic Program Repair—0
AdaptivePaste: Code Adaptation through Learning Semantics-aware Variable Usage Representations—0
Neural Program Repair: Systems, Challenges and Solutions—0
Enabling Automatic Repair of Source Code Vulnerabilities Using Data-Driven Methods—0
MultiFix: Learning to Repair Multiple Errors by Optimal Alignment Learning—0
GRAPHIX: A Pre-trained Graph Edit Model for Automated Program Repair—0
Mapping the Structure and Evolution of Software Testing Research Over the Past Three Decades—0
Grammar-Based Patches Generation for Automated Program Repair—0
TFix: Learning to Fix Coding Errors with a Text-to-Text TransformerCode1
Tea: Program Repair Using Neural Network Based on Program Information Attention Matrix—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