CrossCode: Multi-level Visual Representations of Computer Program Execution

要旨

Program visualizations help to form useful mental models of how programs work, and to reason and debug code. But these visualizations exist at a fixed level of abstraction, e.g., line-by-line. In contrast, programmers switch between many levels of abstraction when inspecting program behavior. Based on results from a formative study of hand-designed program visualizations, we designed CrossCode, a web-based program visualization system for JavaScript that leverages structural cues in syntax, control flow, and data flow to aggregate and navigate program execution across multiple levels of abstraction. In an exploratory qualitative study with experts, we found that CrossCode enabled participants to maintain a strong sense of place in program execution, was conducive to explaining program behavior, and helped track changes and updates to the program state.

著者
Devamardeep Hayatpur
University of California, San Diego, La Jolla, California, United States
Daniel Wigdor
University of Toronto, Toronto, Ontario, Canada
Haijun Xia
University of California, San Diego, San Diego, California, United States
論文URL

https://doi.org/10.1145/3544548.3581390

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Programming

Room Y01+Y02
6 件の発表
2023-04-25 01:35:00
2023-04-25 03:00:00