Enhancing developer interactions with programming screencasts through accurate code extraction

Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have...

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Main Authors: BAO, Lingfeng, PAN, Shengyi, XING, Zhenchang, XIA, Xin, LO, David, YANG, Xiaohu
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Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/sis_research/5632
https://ink.library.smu.edu.sg/context/sis_research/article/6635/viewcontent/Enhancing_Developer_Interactions_pv.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-66352021-01-19T05:58:56Z Enhancing developer interactions with programming screencasts through accurate code extraction BAO, Lingfeng PAN, Shengyi XING, Zhenchang XIA, Xin LO, David YANG, Xiaohu Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have for interacting with the code. Many studies apply the Optical Character Recognition (OCR) technique to convert screen images into text, which can be easily searched and indexed. However, we observe that the noise in the screen images significantly affects the quality of OCRed code.In this paper, we develop a tool named psc2code, which has two components, denoising code extraction from screencasts and enhancing programming video interaction. Experiment results on 1142 programming screencasts from YouTube show psc2code can effectively identify frames containing valid code region with a F1-score of 0.88 and improve the quality of OCRed code by fixing 46% of the errors. We also conduct a user study to evaluate the applicability of psc2code in enhancing video interaction, which shows it helps participants learn the knowledge in tutorials more efficiently. 2020-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5632 info:doi/10.1145/3368089.3417925 https://ink.library.smu.edu.sg/context/sis_research/article/6635/viewcontent/Enhancing_Developer_Interactions_pv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Programming videos code extraction computer vision Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Programming
videos
code extraction
computer vision
Software Engineering
spellingShingle Programming
videos
code extraction
computer vision
Software Engineering
BAO, Lingfeng
PAN, Shengyi
XING, Zhenchang
XIA, Xin
LO, David
YANG, Xiaohu
Enhancing developer interactions with programming screencasts through accurate code extraction
description Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have for interacting with the code. Many studies apply the Optical Character Recognition (OCR) technique to convert screen images into text, which can be easily searched and indexed. However, we observe that the noise in the screen images significantly affects the quality of OCRed code.In this paper, we develop a tool named psc2code, which has two components, denoising code extraction from screencasts and enhancing programming video interaction. Experiment results on 1142 programming screencasts from YouTube show psc2code can effectively identify frames containing valid code region with a F1-score of 0.88 and improve the quality of OCRed code by fixing 46% of the errors. We also conduct a user study to evaluate the applicability of psc2code in enhancing video interaction, which shows it helps participants learn the knowledge in tutorials more efficiently.
format text
author BAO, Lingfeng
PAN, Shengyi
XING, Zhenchang
XIA, Xin
LO, David
YANG, Xiaohu
author_facet BAO, Lingfeng
PAN, Shengyi
XING, Zhenchang
XIA, Xin
LO, David
YANG, Xiaohu
author_sort BAO, Lingfeng
title Enhancing developer interactions with programming screencasts through accurate code extraction
title_short Enhancing developer interactions with programming screencasts through accurate code extraction
title_full Enhancing developer interactions with programming screencasts through accurate code extraction
title_fullStr Enhancing developer interactions with programming screencasts through accurate code extraction
title_full_unstemmed Enhancing developer interactions with programming screencasts through accurate code extraction
title_sort enhancing developer interactions with programming screencasts through accurate code extraction
publisher Institutional Knowledge at Singapore Management University
publishDate 2020
url https://ink.library.smu.edu.sg/sis_research/5632
https://ink.library.smu.edu.sg/context/sis_research/article/6635/viewcontent/Enhancing_Developer_Interactions_pv.pdf
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