Back to articles
Articles
Volume: 32 | Article ID: art00015
Image
Real-time Whiteboard Coding on Mobile Devices
  DOI :  10.2352/ISSN.2470-1173.2020.8.IMAWM-309  Published OnlineJanuary 2020
Abstract

Mobile devices typically support input from virtual keyboards or pen-based technologies, allowing handwriting to be a potentially viable text input solution for programming on touchscreen devices. The major problem, however, is that handwriting recognition systems are built to take advantage of the rules of natural languages rather than programming languages. In addition, mobile devices are also inherently restricted by the limitation of screen size and the inconvenient use of a virtual keyboard. In this work, we create a novel handwriting-to-code transformation system on a mobile platform to recognize and analyze source code written directly on a whiteboard or a piece of paper. First, the system recognizes and further compiles the handwritten source code into an executable program. Second, a friendly graphical user interface (GUI) is provided to visualize how manipulating different sections of code impacts the program output. Finally, the coding system supports an automatic error detection and correction mechanism to help address the common syntax and spelling errors during the process of whiteboard coding. The mobile application provides a flexible and user-friendly solution for realtime handwriting-based programming for learners under various environments where the keyboard or touchscreen input is not preferred.

Subject Areas :
Views 6
Downloads 0
 articleview.views 6
 articleview.downloads 0
  Cite this article 

Xunyu Pan, Colin Crowe, Toby Myers, Emily Jetton, "Real-time Whiteboard Coding on Mobile Devicesin Proc. IS&T Int’l. Symp. on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World,  2020,  pp 309-1 - 309-6,  https://doi.org/10.2352/ISSN.2470-1173.2020.8.IMAWM-309

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2020
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA