A Survey of Interaction Techniques and Devices for Large High Resolution Displays

Innovations in large high-resolution wall-sized displays have been yielding benefits to visualizations in industry and academia, leading to a rapidly growing increase of their implementations. In scenarios such as these, the displayed visual information tends to be larger than the users field of view, hence the necessity to move away from traditional interaction methods towards more suitable interaction devices and techniques. This paper aspires to explore the state-of-the-art with respect to such technologies for large high-resolution displays

Zone-based formal specification and timing analysis of real-time self-adaptive systems

Self-adaptive software systems are able to autonomously adapt their behavior at run-time to react to internal dynamics and to uncertain and changing environment conditions. Formal specification and verification of self-adaptive systems are tasks generally very difficult to carry out, especially when involving time constraints. In this case, in fact, the system correctness depends also on the time associated with events. This article introduces the Zone-based Time Basic Petri nets specification formalism. The formalism adopts timed adaptation models to specify self-adaptive behavior with temporal constraints, and relies on a zone-based modeling approach to support separation of concerns. Zones identified during the modeling phase can be then used as modules either in isolation, to verify intra-zone properties, or all together, to verify inter-zone properties over the entire system. In addition, the framework allows the verification of (timed) robustness properties to guarantee self-healing capabilities when higher levels of reliability and availability are required to the system, especially when dealing with time-critical systems. This article presents also the ZAFETY tool, a Java software implementation of the proposed framework, and the validation and experimental results obtained in modeling and verifying two time-critical self-adaptive systems: the Gas Burner system and the Unmanned Aerial Vehicle system

Interactive Visualization Lenses:: Natural Magic Lens Interaction for Graph Visualization

Information visualization is an important research field concerned with making sense and inferring knowledge from data collections. Graph visualizations are specific techniques for data representation relevant in diverse application domains among them biology, software-engineering, and business finance. These data visualizations benefit from the display space provided by novel interactive large display environments. However, these environments also cause new challenges and result in new requirements regarding the need for interaction beyond the desktop and according redesign of analysis tools. This thesis focuses on interactive magic lenses, specialized locally applied tools that temporarily manipulate the visualization. These may include magnification of focus regions but also more graph-specific functions such as pulling in neighboring nodes or locally reducing edge clutter. Up to now, these lenses have mostly been used as single-user, single-purpose tools operated by mouse and keyboard. This dissertation presents the extension of magic lenses both in terms of function as well as interaction for large vertical displays. In particular, this thesis contributes several natural interaction designs with magic lenses for the exploration of graph data in node-link visualizations using diverse interaction modalities. This development incorporates flexible switches between lens functions, adjustment of individual lens properties and function parameters, as well as the combination of lenses. It proposes interaction techniques for fluent multi-touch manipulation of lenses, controlling lenses using mobile devices in front of large displays, and a novel concept of body-controlled magic lenses. Functional extensions in addition to these interaction techniques convert the lenses to user-configurable, personal territories with use of alternative interaction styles. To create the foundation for this extension, the dissertation incorporates a comprehensive design space of magic lenses, their function, parameters, and interactions. Additionally, it provides a discussion on increased embodiment in tool and controller design, contributing insights into user position and movement in front of large vertical displays as a result of empirical investigations and evaluations.Informationsvisualisierung ist ein wichtiges Forschungsfeld, das das Analysieren von Daten unterstützt. Graph-Visualisierungen sind dabei eine spezielle Variante der Datenrepräsentation, deren Nutzen in vielerlei Anwendungsfällen zum Einsatz kommt, u.a. in der Biologie, Softwareentwicklung und Finanzwirtschaft. Diese Datendarstellungen profitieren besonders von großen Displays in neuen Displayumgebungen. Jedoch bringen diese Umgebungen auch neue Herausforderungen mit sich und stellen Anforderungen an Nutzerschnittstellen jenseits der traditionellen Ansätze, die dadurch auch Anpassungen von Analysewerkzeugen erfordern. Diese Dissertation befasst sich mit interaktiven „Magischen Linsen“, spezielle lokal-angewandte Werkzeuge, die temporär die Visualisierung zur Analyse manipulieren. Dabei existieren zum Beispiel Vergrößerungslinsen, aber auch Graph-spezifische Manipulationen, wie das Anziehen von Nachbarknoten oder das Reduzieren von Kantenüberlappungen im lokalen Bereich. Bisher wurden diese Linsen vor allem als Werkzeug für einzelne Nutzer mit sehr spezialisiertem Effekt eingesetzt und per Maus und Tastatur bedient. Die vorliegende Doktorarbeit präsentiert die Erweiterung dieser magischen Linsen, sowohl in Bezug auf die Funktionalität als auch für die Interaktion an großen, vertikalen Displays. Insbesondere trägt diese Dissertation dazu bei, die Exploration von Graphen mit magischen Linsen durch natürliche Interaktion mit unterschiedlichen Modalitäten zu unterstützen. Dabei werden flexible Änderungen der Linsenfunktion, Anpassungen von individuellen Linseneigenschaften und Funktionsparametern, sowie die Kombination unterschiedlicher Linsen ermöglicht. Es werden Interaktionstechniken für die natürliche Manipulation der Linsen durch Multitouch-Interaktion, sowie das Kontrollieren von Linsen durch Mobilgeräte vor einer Displaywand vorgestellt. Außerdem wurde ein neuartiges Konzept körpergesteuerter magischer Linsen entwickelt. Funktionale Erweiterungen in Kombination mit diesen Interaktionskonzepten machen die Linse zu einem vom Nutzer einstellbaren, persönlichen Arbeitsbereich, der zudem alternative Interaktionsstile erlaubt. Als Grundlage für diese Erweiterungen stellt die Dissertation eine umfangreiche analytische Kategorisierung bisheriger Forschungsarbeiten zu magischen Linsen vor, in der Funktionen, Parameter und Interaktion mit Linsen eingeordnet werden. Zusätzlich macht die Arbeit Vor- und Nachteile körpernaher Interaktion für Werkzeuge bzw. ihre Steuerung zum Thema und diskutiert dabei Nutzerposition und -bewegung an großen Displaywänden belegt durch empirische Nutzerstudien

Automated test-based learning and verification of performance models for microservices systems

Effective and automated verification techniques able to provide assurances of performance and scalability are highly demanded in the context of microservices systems. In this paper, we introduce a methodology that applies specification-driven load testing to learn the behavior of the target microservices system under multiple deployment configurations. Testing is driven by realistic workload conditions sampled in production. The sampling produces a formal description of the users' behavior through a Discrete Time Markov Chain. This model drives multiple load testing sessions that query the system under test and feed a Bayesian inference process which incrementally refines the initial model to obtain a complete specification from run-time evidence as a Continuous Time Markov Chain. The complete specification is then used to conduct automated verification by using probabilistic model checking and to compute a configuration score that evaluates alternative deployment options. This paper introduces the methodology, its theoretical foundation, and the toolchain we developed to automate it. Our empirical evaluation shows its applicability, benefits, and costs on a representative microservices system benchmark. We show that the methodology detects performance issues, traces them back to system-level requirements, and, thanks to the configuration score, provides engineers with insights on deployment options. The comparison between our approach and a selected state-of-the-art baseline shows that we are able to reduce the cost up to 73% in terms of number of tests. The verification stage requires negligible execution time and memory consumption. We observed that the verification of 360 system-level requirements took ~1 minute by consuming at most 34 KB. The computation of the score involved the verification of ~7k (automatically generated) properties verified in ~72 seconds using at most ~50 KB. (C)& nbsp;2022 The Author(s). Published by Elsevier Inc.& nbsp

DEPLOYING, IMPROVING AND EVALUATING EDGE BUNDLING METHODS FOR VISUALIZING LARGE GRAPHS

A tremendous increase in the scale of graphs has been witnessed in a wide range of fields, which demands efficient and effective visualization techniques to assist users in better understandings of large graphs. Conventional node-link diagrams are often used to visualize graphs, whereas excessive edge crossings can easily incur severe visual clutter in the node-link diagram of a large graph. Edge bundling can effectively remedy visual clutter and reveal high-level graph structures. Although significant efforts have been devoted to developing edge bundling, three challenging problems remain. First, edge bundling techniques are often computationally expensive and are not easy to deploy for web-based applications. The state-of-the-art edge bundling methods often require special system supports and techniques such as high-end GPU acceleration for large graphs, which makes these methods less portable, especially for ubiquitous mobile devices. Second, the quantitative quality of edge bundling results is barely assessed in the literature. Currently, the comparison of edge bundling mainly focuses on computational performance and perceptual results. Third, although the family of edge bundling techniques has a rich set of bundling layout, there is a lack of a generic method to generate different styles of edge bundling. In this research, I aim to address these problems and have made the following contributions. First, I provide an efficient framework to deploy edge bundling for web-based platforms by exploiting standard graphics hardware functions and libraries. My framework can generate high-quality edge bundling results on web-based platforms, and achieve a speedup of 50X compared to the previous state-of-the-art edge bundling method on a graph with half of a million edges. Second, I propose a new moving least squares based approach to lower the algorithm complexity of edge bundling. In addition, my approach can generate better bundling results compared to other methods based on a quality metric. Third, I provide an information-theoretic metric to evaluate the edge bundling methods. I leverage information theory in this metric. With my information-theoretic metric, domain users can choose appropriate edge bundling methods with proper parameters for their applications. Last but not least, I present a deep learning framework for edge bundling visualizations. Through a training process that learns the results of a specific edge bundling method, my deep learning framework can infer the final layout of the edge bundling method. My deep learning framework is a generic framework that can generate the corresponding results of different edge bundling methods. Adviser: Hongfeng Y