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

2026-01-15

AI Summary

This study addresses the challenge of intuitively representing complex interdependencies among simulation parameters in traditional tabular interfaces, which often lead to configuration errors and excessive cognitive load. To mitigate this, the work proposes the first application of an interactive Sankey diagram for visualizing parameter dependencies. A functional interface prototype was developed and evaluated against a conventional table-based approach using the PURE heuristic evaluation method, with a focus on user comprehension efficiency. Empirical results demonstrate that the Sankey diagram significantly reduces cognitive load by 51% and decreases interaction steps by 56%, thereby substantially enhancing the understandability and usability of configuration-intensive systems. This approach establishes a novel paradigm for visualizing parameter dependencies in complex simulation environments.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Model-Based Reasoning

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Web Mining and Content Analysis: Web data generation and simulation

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.

Problem

• parameter dependencies
• program comprehension
• configuration-intensive software
• software visualization
• user interaction

Innovation

• Sankey diagrams
• parameter dependencies
• software visualization
• program comprehension
• cognitive load