dorsal/arxiv
View SchemaTables or Sankey Diagrams? Investigating User Interaction with Different Representations of Simulation Parameters
| Authors | Choro Ulan uulu, Mikhail Kulyabin, Katharina M Zeiner, Jan Joosten, Nuno Miguel Martins Pacheco, Filippos Petridis, Rebecca Johnson, Jan Bosch, Helena Holmström Olsson |
|---|---|
| Categories | |
| ArXiv ID | 2601.10232vv1 |
| URL | https://arxiv.org/abs/2601.10232 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
Abstract
Understanding complex parameter dependencies is critical for effective configuration and maintenance of software systems across diverse domains - from Computer-Aided Engineering (CAE) to cloud infrastructure and database management. However, legacy tabular interfaces create a major bottleneck: engineers cannot easily comprehend how parameters relate across the system, leading to inefficient workflows, costly configuration errors, and reduced system trust - a fundamental program comprehension challenge in configuration-intensive software. This research evaluates whether interactive Sankey diagrams can improve comprehension of parameter dependencies compared to traditional spreadsheet interfaces. We employed a heuristic evaluation using the PURE method with three expert evaluators (UX design, simulation, and software development specialists) to compare a Sankey-based prototype to traditional tabular representations for core engineering tasks. Our key contribution demonstrates that flow-based parameter visualizations significantly reduce cognitive load (51% lower PURE scores) and interaction complexity (56% fewer steps) compared to traditional tables, while making parameter dependencies immediately visible rather than requiring mental reconstruction. By explicitly visualizing parameter relationships, Sankey diagrams address a core software visualization challenge: helping users comprehend complex system configurations without requiring deep tool-specific knowledge. While demonstrated through CAE software, this research contributes to program comprehension and software visualization by showing that dependency-aware visualizations can significantly improve understanding of configuration-intensive systems. The findings have implications for any software domain where comprehending complex parameter relationships is essential for effective system use and maintenance.
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"abstract": "Understanding complex parameter dependencies is critical for effective configuration and maintenance of software systems across diverse domains - from Computer-Aided Engineering (CAE) to cloud infrastructure and database management. However, legacy tabular interfaces create a major bottleneck: engineers cannot easily comprehend how parameters relate across the system, leading to inefficient workflows, costly configuration errors, and reduced system trust - a fundamental program comprehension challenge in configuration-intensive software. This research evaluates whether interactive Sankey diagrams can improve comprehension of parameter dependencies compared to traditional spreadsheet interfaces. We employed a heuristic evaluation using the PURE method with three expert evaluators (UX design, simulation, and software development specialists) to compare a Sankey-based prototype to traditional tabular representations for core engineering tasks. Our key contribution demonstrates that flow-based parameter visualizations significantly reduce cognitive load (51% lower PURE scores) and interaction complexity (56% fewer steps) compared to traditional tables, while making parameter dependencies immediately visible rather than requiring mental reconstruction. By explicitly visualizing parameter relationships, Sankey diagrams address a core software visualization challenge: helping users comprehend complex system configurations without requiring deep tool-specific knowledge. While demonstrated through CAE software, this research contributes to program comprehension and software visualization by showing that dependency-aware visualizations can significantly improve understanding of configuration-intensive systems. The findings have implications for any software domain where comprehending complex parameter relationships is essential for effective system use and maintenance.",
"arxiv_id": "2601.10232",
"authors": [
"Choro Ulan uulu",
"Mikhail Kulyabin",
"Katharina M Zeiner",
"Jan Joosten",
"Nuno Miguel Martins Pacheco",
"Filippos Petridis",
"Rebecca Johnson",
"Jan Bosch",
"Helena Holmstr\u00f6m Olsson"
],
"categories": [
"cs.HC",
"cs.SE"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "Tables or Sankey Diagrams? Investigating User Interaction with Different Representations of Simulation Parameters",
"url": "https://arxiv.org/abs/2601.10232",
"version": "v1"
},
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"source": {
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"id": "arXiv Dataset",
"type": "Model",
"variant": "snapshot-2026-01-17",
"version": "0.1.0"
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"user_id": 1000002
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