Papers with Code 아카이브
Program Repair
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 4
- 보존된 평가 기록
- 8
Task of teaching ML models to modify an existing program to fix a bug in a given code.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ARiSE-Lab/Patch-as-translation
공식 코드https://github.com/ASSERT-KTH/elle-elle-aime
공식 코드RepairBench: Leaderboard of Frontier Models for Program Repair
https://github.com/ASSERT-KTH/repairbench
공식 코드RepairBench: Leaderboard of Frontier Models for Program Repair
https://github.com/OpenAutoCoder/Agentless
공식 코드Agentless: Demystifying LLM-based Software Engineering Agents
https://github.com/PierreBlanchart/CMBDTC
공식 코드An exact counterfactual-example-based approach to tree-ensemble models interpretability
https://github.com/RGAI-USZ/JS-patch-exploration-APR2021
공식 코드Exploring Plausible Patches Using Source Code Embeddings in JavaScript
https://github.com/SEED-VT/FedDebug
공식 코드FedDebug: Systematic Debugging for Federated Learning Applications
https://github.com/YerbaPage/MGDebugger
공식 코드From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
https://github.com/ali-ghanbari/deepmufl-ase-2023
공식 코드https://github.com/ant-research/BayesianLinearAttributionForRootCauseLocalization_BALANCE
공식 코드BALANCE: Bayesian Linear Attribution for Root Cause Localization
https://github.com/arabelatso/deepfd
공식 코드DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs
https://github.com/arbaazQureshi/attention_based_multimodal_fusion_for_estimating_depression
공식 코드Assessing the Effectiveness of Syntactic Structure to Learn Code Edit Representations
https://github.com/arise-lab/semcoder
공식 코드SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning
https://github.com/assert-kth/repairllama
공식 코드RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
https://github.com/chengjunyan1/graph-sparse-transformer
공식 코드Graph Conditioned Sparse-Attention for Improved Source Code Understanding
https://github.com/cuhk-shenzhen-se/d4c
공식 코드https://github.com/deepdiagnosis/icse2022
공식 코드https://github.com/fsoft-ai4code/hyperagent
공식 코드HyperAgent: Generalist Software Engineering Agents to Solve Coding Tasks at Scale
https://github.com/fudanselab/linuxflbench
공식 코드Benchmarking and Enhancing LLM Agents in Localizing Linux Kernel Bugs
https://github.com/giganticode/out_of_context_paper_data
공식 코드Out of Context: How important is Local Context in Neural Program Repair?
https://github.com/gintool/gin
공식 코드Enhancing Genetic Improvement Mutations Using Large Language Models
https://github.com/google-research/google-research/tree/master/cubert
공식 코드https://github.com/google-research/google-research/tree/master/gfsa
공식 코드Learning Graph Structure With A Finite-State Automaton Layer
https://github.com/google-research/google-research/tree/master/ipagnn
공식 코드Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
https://github.com/ise-uiuc/Repilot
공식 코드https://github.com/keowang/dynamic-program-embedding
공식 코드https://github.com/koutchemecharles/gaied_nips23
공식 코드https://github.com/kth/SequenceR
공식 코드SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair
https://github.com/lin-tan/CURE
공식 코드CURE: Code-Aware Neural Machine Translation for Automatic Program Repair
https://github.com/lin-tan/knod
공식 코드KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair
https://github.com/lin-tan/llm-vul
공식 코드How Effective Are Neural Networks for Fixing Security Vulnerabilities
https://github.com/llm4se/obfuscated-chatgpt-experiments
공식 코드Breaking the Silence: the Threats of Using LLMs in Software Engineering
https://github.com/mboehme/learn2fix
공식 코드https://github.com/mdrafiqulrabin/CI-Memorization
공식 코드Memorization and Generalization in Neural Code Intelligence Models
https://github.com/mdrafiqulrabin/SIVAND
공식 코드Understanding Neural Code Intelligence Through Program Simplification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.