State-of-the-art of ML-based Code Completion Approaches (2018 ~ 2021)

We compared the state-of-the-art of Machine Learning-based code completion approaches (mostly from 2018 to 2021)

Online version: SOA Code Completion

The survey is used in the below paper:

Kim Tuyen Le, Gabriel Rashidi, and Artur Andrzejak. A Methodology for Refined Evaluation of ML-based Code Completion Approaches. In Special Issue on Programming Language Processing, Data Mining and Knowledge Discovery.

Please read the README-SOA-CodeCompletion.txt file for detailed information of structuring the SOA table.