CodeTF: One-stop Transformer Library for State-of-the-art Code LLM
A curated list of papers, theses, datasets, and tools related to the application of Machine Learning for Software Engineering
Must-read papers on Repository-level Code Generation & Issue Resolution 🔥
RepairAgent is an autonomous LLM-based agent for software repair.
[ASE 2025] Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive Prototyping
DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation
This repository provide the studies on the security of language models for code (CodeLMs).
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
[FSE 2026] EfficientUICoder: Efficient MLLM-based UI Code Generation via Input and Output Token Compression
Explainable AI for Software Engineering: A Hands-on Guide on How to Make Software Analytics More Practical, Explainable, and Actionable (https://xai4se.github.io)
[SIGKDD 2026] ComUICoder: Component-based Reusable UI Code Generation for Complex Websites via Semantic Segmentation and Element-wise Feedback
Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022
[TOSEM 2025] Datasets and models for TD detection in Java using comment and source code
Repository for TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammar (ACL'26 Main).
FPLearner is a DL-based tool to predict performance and accuracy of mixed-precision programs that can be used in dynamic precision tuners to save time.
[FSE 2026] Do Not Treat Code as Natural Language: Implications for Repository-Level Code Generation and Beyond
🎓 Automatically Update AI4Science Papers by Category Daily using Github Actions
GitHub repository for our work What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond
[ICSE 2026] TestWeaver: Execution-aware, Feedback-driven Regression Testing Generation with Large Language Models