2019/07/05 by Rebecca Faust, Katherine E. Isaacs, Faust, Rebecca +7
Computer Science · Decision Sciences · #Data Visualization and Analytics #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Scientific Computing and Data Management #Software Engineering (cs.SE) #Software Engineering Research
paper · pdf · doi:10.48550/arxiv.1907.02872
openalex publication_date 2019/07/05 · openalex created_date 2020/10/01 · openalex updated_date 2026/07/28
Debugging is famously one the hardest parts in programming. In this paper, we tackle the question: what does a debugging environment look like when we take interactive visualization as a central design principle? We introduce Anteater, an interactive visualization system for tracing and exploring the execution of Python programs. Existing systems often have visualization components built on top of an existing infrastructure. In contrast, Anteater's organization of trace data enables an intermediate representation which can be leveraged to automatically synthesize a variety of visualizations and interactions. These interactive visualizations help with tasks such as discovering important structures in the execution and understanding and debugging unexpected behaviors. To assess the utility of Anteater, we conducted a participant study where programmers completed tasks on their own python programs using Anteater. Finally, we discuss limitations and where further research is needed.