2022/05/25 by Jan Baumeister, Bernd Finkbeiner, Baumeister, Jan +5
Computer Science · Decision Sciences · #Anomaly Detection Techniques and Applications #Data Visualization and Analytics #FOS: Computer and information sciences #Formal Languages and Automata Theory (cs.FL) #Simulation Techniques and Applications
paper · pdf · doi:10.48550/arxiv.2205.12823
openalex publication_date 2022/05/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Stream-based runtime monitors are used in safety-critical applications such as Unmanned Aerial Systems (UAS) to compute comprehensive statistics and logical assessments of system health that provide the human operator with critical information in hand-over situations. In such applications, a visual display of the monitoring data can be much more helpful than the textual alerts provided by a more traditional user interface. This visualization requires extensive real-time data processing, which includes the synchronization of data from different streams, filtering and aggregation, and priorization and management of user attention. We present a visualization approach for the \rtlola monitoring framework. Our approach is based on the principle that the necessary data processing is the responsibility of the monitor itself, rather than the responsibility of some external visualization tool. We show how the various aspects of the data transformation can be described as RTLola stream equations and linked to the visualization component through a bidirectional synchronous interface. In our experience, this approach leads to highly informative visualizations as well as to understandable and easily maintainable monitoring code.