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

doi:10.13190/j.jbupt.2019-125

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (6): 70-75.doi: 10.13190/j.jbupt.2019-125

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

LIU Pai, SUN Yan, REN Wei

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

Abstract

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

CLC Number:

TP301.6

LIU Pai, SUN Yan, REN Wei. An ANTLR-Based Feature Extraction and Detection System for Scratch3.0[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(6): 70-75.

References

[1] Fowler M. Refactoring:improving the design of existing code[M].[S.l.]:Addison-Wesley Professional, 2018.
[2] Meerbaum-Salant O, Armoni M, Ben-Ari M. Habits of programming in scratch[C]//Proceedings of the 16^th Annual Joint Conference on Innovation and Technology in Computer Science Education-ITiCSE'11. New York:ACM Press, 2011:168-172.
[3] Wolz U, Hallberg C, Taylor B. Scrape:a tool for visualizing the code of Scratch programs[C]//Poster Presented at the 42^nd ACM Technical Symposium on Computer Science Education. Dallas:[s.n.], 2011:100-110.
[4] Boe B, Hill C, Len M, et al. Hairball:lint-inspired static analysis of scratch projects[C]//Proceeding of the 44^th ACM Technical Symposium on Computer Science Education.[S. l.]:ACM, 2013:215-220.
[5] Techapalokul P, Tilevich E. Quality hound:an online code smell analyzer for scratch programs[C]//2017 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). New York:IEEE Press, 2017:337-338.
[6] Hermans F, Stolee K T, Hoepelman D. Smells in block-based programming languages[C]//2016 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). New York:IEEE Press, 2016:68-72.
[7] Techapalokul P, Tilevich E. Understanding recurring quality problems and their impact on code sharing in block-based software[C]//2017 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). New York:IEEE Press, 2017:43-51.
[8] Parr T. The definitive ANTLR 4 reference[M].[S.l.]:Pragmatic Bookshelf, 2013.
[9] Wang Xiaolei, Huang Xinmin, Yan Chang, et al. Analysis of scratch project with process data[C]//2018 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW). New York:IEEE Press, 2018:1-2.
[10] Chang Zhong, Sun Yan, Wu Tinyu, et al. Scratch analysis tool(SAT):a modern scratch project analysis tool based on ANTLR to assess computational thinking skills[C]//2018 14^th International Wireless Communications & Mobile Computing Conference (IWCMC). New York:IEEE Press, 2018:950-955.

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

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