Flow2Code: From Hand-drawn Flowcharts to Code Execution
Abstract
Flowcharts play an important role when learning to program by conveying algorithms graphically and making them easy to read and understand. Computer-based owchart design requires the user to learn the so ware rst, which o en results in a steep learning curve. Paper-drawn owcharts don't provide feedback. We propose a system that allows users to draw their owcharts directly on paper combined with a mobile phone app that takes a photo of the owchart, interprets it, and generates and executes the resulting code. Flow2Code uses o -line sketch recognition and computer vision algorithms to recognize owcharts drawn on paper. To gain practice and feedback with owcharts, the user needs only a pencil, white paper, and a mobile device. e paper describes a tested system and algorithmic model for recognizing and interpreting o ine owcharts as well as a novel geometric feature, Axis Aligned Score (AAS), that enables fast accurate recognition of various quadrilaterals.
BibTeX
@inproceedings {10.1145:3092907.3092911,
booktitle = {Sketch-Based Interfaces and Modeling},
editor = {Holger Winnemoeller and Lyn Bartram},
title = {{Flow2Code: From Hand-drawn Flowcharts to Code Execution}},
author = {Herrera-Camara, Jorge-Ivan and Hammond, Tracy},
year = {2017},
publisher = {Association for Computing Machinery, Inc (ACM)},
ISSN = {1812-3503},
ISBN = {978-1-4503-5080-8},
DOI = {10.1145/3092907.3092911}
}
booktitle = {Sketch-Based Interfaces and Modeling},
editor = {Holger Winnemoeller and Lyn Bartram},
title = {{Flow2Code: From Hand-drawn Flowcharts to Code Execution}},
author = {Herrera-Camara, Jorge-Ivan and Hammond, Tracy},
year = {2017},
publisher = {Association for Computing Machinery, Inc (ACM)},
ISSN = {1812-3503},
ISBN = {978-1-4503-5080-8},
DOI = {10.1145/3092907.3092911}
}