Tables or Sankey Diagrams? Investigating User Interaction with Different Representations of Simulation Parameters

• URL: http://arxiv.org/abs/2601.10232v1
• Date: Thu, 15 Jan 2026 09:46:02 GMT
• Title: Tables 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,
• Abstract summary: This research evaluates whether interactive Sankey diagrams can improve comprehension of parameter dependencies.<n>By explicitly visualizing parameter relationships, Sankey diagrams address a core software visualization challenge.
• Score: 3.0049184484925604
• 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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