北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (6): 70-75.doi: 10.13190/j.jbupt.2019-125

• 论文 • 上一篇    下一篇

一种基于ANTLR的面向Scratch3.0的特征提取和检测系统

刘派, 孙岩, 任玮   

  1. 北京邮电大学 北京市智能通信软件与多媒体重点实验室, 北京 100876
  • 收稿日期:2019-11-22 出版日期:2019-12-28 发布日期:2019-11-15
  • 通讯作者: 孙岩(1970-),女,教授,博士生导师,E-mail:sunyan@bupt.edu.cn. E-mail:sunyan@bupt.edu.cn
  • 作者简介:刘派(1993-),男,硕士生.
  • 基金资助:
    国家自然科学基金项目(61672109,61772085,61877005)

An ANTLR-Based Feature Extraction and Detection System for Scratch3.0

LIU Pai, SUN Yan, REN Wei   

  1. Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2019-11-22 Online:2019-12-28 Published:2019-11-15

摘要: Scratch是一种适合少年儿童使用的可视化编程语言,并在全球的编程教育领域中受到广泛地关注.由于目前各大教育编程平台都开始使用Scratch3.0版本,而已有的特征提取和检测系统并不支持新版本,为此,提出了一种基于链表数据结构和一种语言识别工具(ANTLR)的面向Scratch3.0的特征提取和检测系统.实验结果表明,该系统可以有效地从项目中提取编程特征,并为学生和教师提供反馈,其检测性能和检测稳定性比Scratch2.0均有所提升.

关键词: Scratch, 一种语言识别工具, 特征检测, 特征提取

Abstract: 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.

Key words: Scratch, another tool for language recognition, feature extraction, feature detection

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