Biblio
Experimentation focused on assessing the value of complex visualisation approaches when compared with alternative methods for data analysis is challenging. The interaction between participant prior knowledge and experience, a diverse range of experimental or real-world data sets and a dynamic interaction with the display system presents challenges when seeking timely, affordable and statistically relevant experimentation results. This paper outlines a hybrid approach proposed for experimentation with complex interactive data analysis tools, specifically for computer network traffic analysis. The approach involves a structured survey completed after free engagement with the software platform by expert participants. The survey captures objective and subjective data points relating to the experience with the goal of making an assessment of software performance which is supported by statistically significant experimental results. This work is particularly applicable to field of network analysis for cyber security and also military cyber operations and intelligence data analysis.
Microservice architectures are steadily gaining adoption in industrial practice. At the same time, performance and resilience are important properties that need to be ensured. Even though approaches for performance and resilience have been developed (e.g., for anomaly detection and fault tolerance), there are no benchmarking environments for their evaluation under controlled conditions. In this paper, we propose a generative platform for benchmarking performance and resilience engineering approaches in microservice architectures, comprising an underlying metamodel, a generation platform, and supporting services for workload generation, problem injection, and monitoring.