[ICML'24] Magicoder: Empowering Code Generation with OSS-Instruct

A curated list of papers, theses, datasets, and tools related to the application of Machine Learning for Software Engineering

[NeurIPS'24] SelfCodeAlign: Self-Alignment for Code Generation

MPLSandbox is an out-of-the-box multi-programming language sandbox designed to provide unified and comprehensive feedback from compiler and analysis tools for LLMs.

For our CCS24 paper 🏆 "ReSym: Harnessing LLMs to Recover Variable and Data Structure Symbols from Stripped Binaries" by Danning Xie, Zhuo Zhang, Nan Jiang, Xiangzhe Xu, Lin Tan, and Xiangyu Zhang. 🏆 ACM SIGSAC Distinguished Paper Award Winner

For our ICSE23 paper "Impact of Code Language Models on Automated Program Repair" by Nan Jiang, Kevin Liu, Thibaud Lutellier, and Lin Tan

Indexing three datasets for GPTScan

✅SRepair: Powerful LLM-based Program Repairer with $0.029/Fixed Bug

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.

Code for ACL (main) paper "JumpCoder: Go Beyond Autoregressive Coder via Online Modification"

Collections of research, benchmarks and tools towards more robust and reliable language models for code; LM4Code; LM4SE; reliable LLM; LLM4Code

Can Language Models Replace Programmers? RepoCod Says ‘Not Yet’ - by Shanchao Liang and Yiran Hu and Nan Jiang and Lin Tan

[AAAI 2025] The official code of the paper "InverseCoder: Unleashing the Power of Instruction-Tuned Code LLMs with Inverse-Instruct"(https://arxiv.org/abs/2407.05700).

WAFFLE: Multi-Modal Model for Automated Front-End Development - by Shanchao Liang and Nan Jiang and Shangshu Qian and Lin Tan

Journey to the WEST (trustWorthy intElligent Software developmenT)