CodeSCAN: ScreenCast ANalysis for Video Programming Tutorials

Alexander Naumann, Alexander Naumann, Felix Hertlein, Felix Hertlein, Jacqueline Höllig, Jacqueline Höllig, Lucas Cazzonelli, Lucas Cazzonelli, Steffen Thoma, Steffen Thoma

2025

Abstract

Programming tutorials in the form of coding screencasts play a crucial role in programming education, serving both novices and experienced developers. However, the video format of these tutorials presents a challenge due to the difficulty of searching for and within videos. Addressing the absence of large-scale and diverse datasets for screencast analysis, we introduce the CodeSCAN dataset. It comprises 12,000 screenshots captured from the Visual Studio Code environment during development, featuring 24 programming languages, 25 fonts, and over 90 distinct themes, in addition to diverse layout changes and realistic user interactions. Moreover, we conduct detailed quantitative and qualitative evaluations to benchmark the performance of Integrated Development Environment (IDE) element detection, color-to-black-and-white conversion, and Optical Character Recognition (OCR). We hope that our contributions facilitate more research in coding screencast analysis, and we make the source code for creating the dataset and the benchmark publicly available at a-nau.github.io/codescan.

Paper Citation

in Harvard Style

Naumann A., Hertlein F., Höllig J., Cazzonelli L. and Thoma S. (2025). CodeSCAN: ScreenCast ANalysis for Video Programming Tutorials. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 269-277. DOI: 10.5220/0013093100003912

in Bibtex Style

@conference{visapp25,
author={Alexander Naumann and Felix Hertlein and Jacqueline Höllig and Lucas Cazzonelli and Steffen Thoma},
title={CodeSCAN: ScreenCast ANalysis for Video Programming Tutorials},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2025},
pages={269-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013093100003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - CodeSCAN: ScreenCast ANalysis for Video Programming Tutorials
SN - 978-989-758-728-3
AU - Naumann A.
AU - Hertlein F.
AU - Höllig J.
AU - Cazzonelli L.
AU - Thoma S.
PY - 2025
SP - 269
EP - 277
DO - 10.5220/0013093100003912
PB - SciTePress