Software development bots for Github. Join the bot revolution! 🌟🤖🌟💞
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Updated
Dec 12, 2023 - Java
Software development bots for Github. Join the bot revolution! 🌟🤖🌟💞
Automatic program repair for Java with generate-and-validate techniques ✌️✌️: jGenProg (2014) - jMutRepair (2016) - jKali (2016) - DeepRepair (2017) - Cardumen (2018) - 3sfix (2018)
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
Repilot, a patch generation tool introduced in the ESEC/FSE'23 paper "Copiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair"
A Systematic Literature Review on Large Language Models for Automated Program Repair
[ICML 2021] Break-It-Fix-It: Unsupervised Learning for Program Repair
Automatic program repair system for Java based on dynamic analysis and code synthesis with SMT. Also contains the code of Dynamoth.
Automatic repair system for static analysis warnings from SonarQube's SonarJava, TDSC 2022 https://arxiv.org/pdf/2103.12033
Automated program repair bibliography, tools and benchmarks.
Research Acceleration Platform that provides interface to multiple state-of-the-art program analysis tools including but not limited to fuzzing, static analysis and program repair.
Artefact for "CoCoNuT: Combining Context-Aware Neural Translation Models using Ensemble for Program Repair."
For our ICSE 2023 paper Impact of Code Language Models on Automated Program Repair
Code of our paper Applying CodeBERT for Automated Program Repair of Java Simple Bugs which is accepted to MSR 2021.
✅SRepair: Powerful LLM-based Program Repairer with $0.029/Fixed Bug
A High-performance, High-extensibility and High-portability APR System
FixMorph is a morphing tool for C source codes which supports automated code-transfer
CPR: A new automated program repair technique based on concolic execution which works on patch abstraction with the sub-optimal goal of refining the patch to less over-fit the initial test cases.
This is an automated transformation inference tool that leverages a big code corpus to guide the abstraction of transformation patterns.
For our ISSTA23 paper "How Effective are Neural Networks for Fixing Security Vulnerabilities?" by Yi Wu, Nan Jiang, Hung Viet Pham, Thibaud Lutellier, Jordan Davis, Lin Tan, Petr Babkin, and Sameena Shah.
Add a description, image, and links to the program-repair topic page so that developers can more easily learn about it.
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