%0 Journal Article
%A LIU Pai
%A REN Wei
%A SUN Yan
%T An ANTLR-Based Feature Extraction and Detection System for Scratch3.0
%D 2019
%R 10.13190/j.jbupt.2019-125
%J Journal of Beijing University of Posts and Telecommunications
%P 70-75
%V 42
%N 6
%X As a visual programming language for children, Scratch has received wide attention in the programming education. Considering that Scratch has evolved to the latest version 3.0 and its storage structure changes significantly from the previous version, the existing methods cannot be directly applied to project analysis. A new feature extraction and detection system based on linked list data structure and another tool for language recognition (ANTLR) was presented to solve the problem. Experimental results show that the system can effectively extract programming features from the projects and provide feedback to students and teachers. Moreover, its detection performance and stability perform better than the original methods in Scratch2.0.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2019-125