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

Explainable AI for Software Engineering: A Hands-on Guide on How to Make Software Analytics More Practical, Explainable, and Actionable (https://xai4se.github.io)

PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022

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.

On the Effectiveness of Machine Learning-based Call Graph Pruning: An Empirical Study

An Extendable Framework for Code Generation and AI4SE Research