Refinement Types for Visualization

Visualizations have become crucial in the contemporary data-driven world as they aid in exploring, verifying, and sharing insights obtained from data. In this paper, we propose a new paradigm of visualization synthesis based on refinement types. Besides input-output examples, users can optionally use refinement-type annotations to constrain the range of valid values in the example visualization or to express complex interactions between different visual components. Our system's outputs include both data transformation and visualization programs that are consistent with refinement-type specifications. To mitigate the scalability challenge during the synthesis process, we introduce a new visualization synthesis algorithm that uses lightweight bidirectional type checking to prune the search space. As we demonstrate experimentally, this new synthesis algorithm results in significant speed-up compared to prior work.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1145/3691620.3695550
Citations
1
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.25

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Refinement Types for Visualization

Jingtao Xia, Junrui Liu, Yu Feng, Yanju Chen et al.
1 citations
Data Visualization and Analytics
0.25
article

Refinement Types for Visualization

Jingtao Xia, Junrui Liu, Yu Feng, Yanju Chen, Nicholas Brown
article en
1 citations

Abstract

Visualizations have become crucial in the contemporary data-driven world as they aid in exploring, verifying, and sharing insights obtained from data. In this paper, we propose a new paradigm of visualization synthesis based on refinement types. Besides input-output examples, users can optionally use refinement-type annotations to constrain the range of valid values in the example visualization or to express complex interactions between different visual components. Our system's outputs include both data transformation and visualization programs that are consistent with refinement-type specifications. To mitigate the scalability challenge during the synthesis process, we introduce a new visualization synthesis algorithm that uses lightweight bidirectional type checking to prune the search space. As we demonstrate experimentally, this new synthesis algorithm results in significant speed-up compared to prior work.

University of California, Santa Barbara (US)
Google
Openalex Percentile: Top 46%
Data Visualization and Analytics
0.25
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Refinement Types for Visualization — Jingtao Xia, Junrui Liu, et al. · (2024) | TGRS Research Map | TGRS