An essential task of an air traffic controller is to manage the traffic flow by predicting future trajectories. Complex traffic patterns are difficult to predict and manage and impose cognitive load on the air traffic controllers. In this work we present an interactive visual analytics interface which facilitates detection and resolution of complex traffic patterns for air traffic controllers. The interface supports air traffic controllers in detecting complex clusters of aircraft and further enables them to visualize and simultaneously compare how different re-routing strategies for each individual aircraft yield reduction of complexity in the entire sector for the next hour. The development of the concepts was supported by the domain-specific feedback we received from six fully licensed and operational air traffic controllers in an iterative design process over a period of 14 months.

Initiating communication and conveying critical information to the human operator is a key problem in human-automation collaboration. This problem is particularly pronounced in time-constrained safety critical domains such as in Air Traffic Management. A visual representation should aid operators understanding why the system initiates the communication, when the operator must act, and the consequences of not responding to the cue. Data glyphs can be used to present multidimensional data, including temporal data in a compact format to facilitate this type of communication. In this paper, we propose a glyph design for communication initialization for highly automated systems in Air Traffic Management, Vessel Traffic Service, and Train Traffic Management. The design was assessed by experts in these domains in three workshop sessions. The results showed that the number of glyphs to be presented simultaneously and the type of situation were domain-specific glyph design aspects that need to be adjusted for each work domain. The results also showed that the core of the glyph design could be reused between domains, and that the operators could successfully interpret the temporal data representations. We discuss similarities and differences in the applicability of the glyph design between the different domains, and finally, we provide some suggestions for future work based on the results from this study.

Abstract Operators in air traffic control facing time‐ and safety‐critical situations call for efficient, reliable and robust real‐time processing and interpretation of complex data. Automation support tools aid controllers in these processes to prevent separation losses between aircraft. Issues of current support tools include limited ‘what‐if’ and ‘what‐else’ probe functionalities in relation to vertical solutions. This work presents the design and evaluation of two visual analytics interfaces that promote contextual awareness and support ‘what‐if’ and ‘what‐else’ probes in the spatio‐temporal domain aiming to improve information integration and support controllers in prioritising conflict resolution. Both interfaces visualize vertical solution spaces against a time‐altitude graph. The main contributions of this paper are: (a) the presentation of two interfaces for supporting conflict solving; (b) the novel representation of how vertical information and aircraft rate of climb and descent affect conflicts and (c) an evaluation and comparison of the interfaces with a traditional air traffic control support system. The evaluation study was performed with domain experts to compare the effects of visualization concepts on operator engagement in processing solutions suggested by the tools. Results show that the visualizations support operators' ability to understand and resolve conflicts. Based on the results, general design guidelines for time‐critical domains are proposed.

Abstract Operational demands in safety‐critical systems impose a risk of failure to the operators especially during urgent situations. Operators of safety‐critical systems learn to make decisions effectively throughout extensive training programs and many years of experience. In the domain of air traffic control, expensive training with high dropout rates calls for research to enhance novices' ability to detect and resolve conflicts in the airspace. While previous researchers have mostly focused on redesigning training instructions and programs, the current paper explores possible benefits of novel visual representations to improve novices' understanding of the situations as well as their decision‐making process. We conduct an experimental evaluation study testing two ecological visual analytics interfaces, developed in a previous study, as support systems to facilitate novice decision‐making. The main contribution of this paper is threefold. First, we describe the application of an ecological interface design approach to the development of two visual analytics interfaces. Second, we perform a human‐in‐the‐loop experiment with forty‐five novices within a simplified air traffic control simulation environment. Third, by performing an expert‐novice comparison we investigate the extent to which effects of the proposed interfaces can be attributed to the subjects' expertise. The results show that the proposed ecological visual analytics interfaces improved novices' understanding of the information about conflicts as well as their problem‐solving performance. Further, the results show that the beneficial effects of the proposed interfaces were more attributable to the visual representations than the users' expertise.

Abstract Static program analysis is in general more precise if it is sensitive to execution contexts (execution paths). But then it is also more expensive in terms of memory consumption. For languages with conditions and iterations, the number of contexts grows exponentially with the program size. This problem is not just a theoretical issue. Several papers evaluating inter-procedural context-sensitive data-flow analysis report severe memory problems, and the path-explosion problem is a major issue in program verification and model checking. In this paper we propose χ-terms as a means to capture and manipulate context-sensitive program information in a data-flow analysis. χ-terms are implemented as directed acyclic graphs without any redundant subgraphs. We introduce the k-approximation and the l-loop-approximation that limit the size of the context-sensitive information at the cost of analysis precision. We prove that every context-insensitive data-flow analysis has a corresponding k,l-approximated context-sensitive analysis, and that these analyses are sound and guaranteed to reach a fixed point. We also present detailed algorithms outlining a compact, redundancy-free, and DAG-based implementation of χ-terms.

Static program analysis is in general more precise if it is sensitive to execution contexts (execution paths). But then it is also more expensive in terms of memory consumption. For languages with conditions and iterations, the number of contexts grows exponentially with the program size. This problem is not just a theoretical issue. Several papers evaluating inter-procedural context-sensitive data-flow analysis report severe memory problems, and the path-explosion problem is a major issue in program verification and model checking. In this paper we propose χ-terms as a means to capture and manipulate context-sensitive program information in a data-flow analysis. χ-terms are implemented as directed acyclic graphs without any redundant subgraphs. To show the efficiency of our approach we run experiments comparing the memory usage of χ-terms with four alternative data structures. Our experiments show that χ-terms clearly outperform all the alternatives in terms of memory efficiency.

In visually demanding environments like working positions in air traffic control, there is a risk of missing important information. Attention support might help to reduce this, but there is a risk that it introduces new issues in the form of distractions or increased visual load. The work presented in this paper explores the concept of Soft Visual Cues, with the aim to make the operator aware of missing information, but doing it discreetly enough only to be noticed when the operator is scanning the area where the information is present, thereby complementing the concepts of attention guidance, alarms, and subtle gaze direction. The qualitative evaluation performed aimed primarily at catching the operators' (air traffic controllers) first impressions. Focus was on air traffic control, but was complemented with vessel traffic service and train control environments and operators. The results from air traffic control showed a preference for symbol property changes related to geometry rather than for colour or opacity changes as soft visual cues. The comparison to the other domains highlighted the contextual dependence, visual context and process context, of the concept.

Geographic visualizations are, due to the limited need for vertical navigation, suitable for touch tables. In this poster we consider the design of interaction design for selection and manipulation through touch on the screen used for the display of 3D geographic visualization-in our case the visualization of and interaction with drone traffic over rural and urban areas-focusing on moving from a monoscopic to a more immersive, stereoscopic touch table, and how this move affects the interaction design. With a monoscopic display our stereoscopic vision uses the graphics to perceive the location of the surface, and touch interaction can naturally and intuitively be performed on top of 3D objects. Moving to stereocopic display, for increased sense of immersion, the graphics no longer provide visual cues about the location of the screen. We argue that this motivates modification of the design principles, with an alternative interaction design as a result.

Social media platforms have created new ways for people to communicate and express themselves. Thus, it is important to explore how e-health related information is generated and disseminated in these platforms. The aim of our current efforts is to investigate the content and flow of information when people in Sweden use Twitter to talk about diabetes related issues. To achieve our goals, we have used data mining and visualization techniques in order to explore, analyze and cluster Twitter data we have collected during a period of 10 months. Our initial results indicate that patients use Twitter to share diabetes related information and to communicate about their disease as an alternative way that complements the traditional channels used by health care professionals.

Cognitive Work Analysis (CWA) is an appropriate approach in design for high-stakes domains, such as air traffic management (ATM) since it focuses on human expert performance in regular and contingency situations. However, CWA is not suitable for the design of a first-of-a-kind system since there is nothing to analyse before the start of the design process. In 2017, unmanned air traffic management (UTM) for intense drone traffic in cities was such a system. Making things worse, the UTM system has to be in place before the traffic, since it provides basic safety. In this research-through-design study, we present conceptual designing as a bootstrapping approach to CWA in the design of a first-of-a-kind UTM system. In a series of co-design workshops, we identified future services, traffic patterns, and regulations that framed the design of UTM system concepts. They were based on combinations of four basic building blocks: points, lines, planes, and volumes. Concepts of point-based control, airport geofences, grid squares, layers, and tubes were discussed. Throughout the conceptual designing, results were documented in an evolving Work Domain Analysis (WDA), which is a cornerstone of CWA. This approach allowed us to bootstrap the CWA for a first-of-a-kind-system.

Abstract We propose a visualization system for incident commanders (ICs) in urban search and rescue scenarios that supports path planning in post‐disaster structures. Utilizing point cloud data acquired from unmanned robots, we provide methods for the assessment of automatically generated paths. As data uncertainty and a priori unknown information make fully automated systems impractical, we present the IC with a set of viable access paths, based on varying risk factors, in a 3D environment combined with visual analysis tools enabling informed decision making and trade‐offs. Based on these decisions, a responder is guided along the path by the IC, who can interactively annotate and reevaluate the acquired point cloud and generated paths to react to the dynamics of the situation. We describe visualization design considerations for our system and decision support systems in general, technical realizations of the visualization components, and discuss the results of two qualitative expert evaluation; one online study with nine search and rescue experts and an eye‐tracking study in which four experts used the system on an application case.

Points-to information is the basis for many analyses and transformations, e.g., for program understanding and optimization. Collections frameworks are part of most modern programming languages' infrastructures and used by many applications. The richness of features and the inherent structure of collection classes affect both performance and precision of points-to analysis negatively. In this paper, we discuss how to replace original collections frameworks with versions specialized for points-to analysis. We implement such a replacement for the Java Collections Framework and support its benefits for points-to analysis by applying it to three different points-to analysis implementations. In experiments, context-sensitive points-to analyses require, on average, 16-24% less time while at the same time being more precise. Context-insensitive analysis in conjunction with in lining also benefits in both precision and analysis cost.

Static program analysis supporting software development is often part of edit-compile-cycles, and precise program analysis is time consuming. Points-to analysis is a data-flow-based static program analysis used to find object references in programs. Its applications include test case generation, compiler optimizations and program understanding, and more. Recent increases in processing power of desktop computers comes mainly from multiple cores. Parallel algorithms are vital for simultaneous use of multiple cores. An efficient parallel points-to analysis requires sufficient work for each processing unit.

Static program analysis usually consists of a number of steps, each producing partial results. For example, the points-to analysis step, calculating object references in a program, usually just provides the input for larger client analyses like reach ability and escape analyses. All these analyses are computationally intense and it is therefore vital to create parallel approaches that make use of the processing power that comes from multiple cores in modern desktop computers. The present paper presents two parallel approaches to increase the efficiency of reach ability analysis and escape analysis, based on a parallel points-to analysis. The experiments show that the two parallel approaches achieve a speed-up of 1.5 for reach ability analysis and 3.8 for escape analysis on 8 cores for a benchmark suite of Java programs.

Points-to information is the basis for many analyses and transformations, e.g., for program understanding and optimization. To justify new analysis techniques, they need to be compared to the state of the art regarding their accuracy and efficiency. Usually, benchmark suites are used to experimentally compare the different techniques. In this paper, we show that the accuracy of two analyses can only be compared in restricted cases, as there is no benchmark suite with exact Points-to information, no Gold Standard, and it is hard to construct one for realistic programs. We discuss the challenges and possible traps that may arise when comparing different Points-to analyses directly with each other, and with over- and under-approximations of a Gold Standard. Moreover, we discuss how different Points-to analyses can be combined to a more precise one. We complement the paper with experiments comparing and combining different static and dynamic Points-to analyses.

This paper shows that existing software metric tools interpret and implement the definitions of object-oriented software metrics differently. This delivers tool-dependent metrics results and has even implications on the results of analyses based on these metrics results. In short, the metrics-based assessment of a software system and measures taken to improve its design differ considerably from tool to tool. To support our case, we conducted an experiment with a number of commercial and free metrics tools. We calculated metrics values using the same set of standard metrics for three software systems of different sizes. Measurements show that, for the same software system and metrics, the metrics values are tool depended. We also defined a (simple) software quality model for "maintainability" based on the metrics selected. It defines a ranking of the classes that are most critical wrt. maintainability. Measurements show that even the ranking of classes in a software system is metrics tool dependent.

Many software engineering applications require points-to analysis. Client applications range from optimizing compilers to program development and testing environments to reverse-engineering tools. In this paper, we present a new context-sensitive approach to points-to analysis where calling contexts are distinguished by the points-to sets analyzed for their target expressions. Compared to other well-known context-sensitive techniques, it is faster - twice as fast as the call string approach and by an order of magnitude faster than the object-sensitive technique - and requires less memory. At the same time, it provides higher precision than the call string technique and is similar in precision to the object-sensitive technique. These statements are confirmed by experiments.

Software maintenance tools for program analysisand refactoring rely on a meta-model capturing the relevantproperties of programs. However, what is considered relevantmay change when the tools are extended with new analyses andrefactorings, and new programming languages. This paper proposesa language independent meta-model and an architecture toconstruct instances thereof, which is extensible for new analyses,refactorings, and new front-ends of programming languages. Dueto the loose coupling between analysis-, refactoring-, and frontend-components, new components can be added independentlyand reuse existing ones. Two maintenance tools implementingthe meta-model and the architecture, VIZZANALYZER and XDEVELOP,serve as a proof of concept.

Software maintenance tools for program analysis and refactoring rely on a metamodel capturing the relevant properties of programs. However, what is considered relevant may change when the tools are extended with new analyses, refactorings, and new programming languages. This paper proposes a language independent metamodel and an architecture to construct instances thereof, which is extensible for new analyses, refactorings, and new front-ends of programming languages. Due to the loose coupling between analysis, refactoring, and front-end components, new components can be added independently and reuse existing ones. Two maintenance tools implementing the metamodel and the architecture, VizzAnalyzer and X-develop, serve as proof of concept.

Software maintenance tools for program-analysis and refactoring rely on a meta-model capturing the relevant properties of programs. However, what is considered relevant may change when the tools are extended with new analyses and refactorings, and new programming languages. This paper proposes a language independent meta-model and an architecture to construct instances thereof which is extensible for new analyses, refactorings, and new front-ends of programming languages. Due to the loose coupling between analysis-, refactoring-, and front-end-components, new components can be added independently and reuse existing ones. Two maintenance tools implementing the meta-model and the architecture, VizzAnalyzer and X-DEVELOP, serve as a proof of concept

In this article we argue that a structured use of perspective descriptions can support a design process. A design perspective is a coherent set of values and aspects emphasized by the designer in a given design situation. We present a generic framework for describing 7 dimensions of perspectives concerning user, artifact, context, activities, communication, central relations, and use qualities that we argue are relevant in a design situation. Subsequently we use this metaperspective to describe four perspectives: tool, architectural, usability, and media perspective distilled from literature sources. By conducting two design workshops, we have evaluated the effects of using perspective descriptions to address the problem of idea generation in the early phases of design. Our analysis shows that the perspectives contain values that can have an important impact on the resulting artifact. By guiding the exploration of the design space, they influence both the artifact's conceptual idea and its use qualities. In our design example, a car game, the conceptual idea of the artifact varied from a goal-oriented tool to a media-based communication experience. Use qualities varied from a task-based flow of action to a format-dependent communication experience. The perspectives served as a synthesis of basic assumptions from the literature and as support to generate conceptually different design ideas. Based on the outcome of our study, we propose an approach for working with design perspectives in design practice, and education. We also present an agenda for research on design perspectives.

The VizzAnalyzer is a framework for analyses and visualizations of software. It has been developed over years, to a great deal by students and PhD students. In between it has been re-engineered to improve the software quality. In this paper, we publish the results of the software quality measurements over different versions of the VizzAnalyzer framework with well established quality metrics. Some metrics uncover qualities we were aiming at in our re-engineering, e.g. maintainability, some others uncover qualities we were deliberately ignoring or did not even think about, e.g. good "object-orientedness". Our measurements validate our expectation: the former metrics significantly improve over the versions whereas the latter contain positive as well as negative surprises

A media terminal box combines digital television and services on the World Wide Web. This device will be available in many homes and the interaction with it occurs via a remote control and a visual presentation. The problem is the navigation difficulties among the huge number of television channels. The aim of this study is to investigate whether spoken commands could solve the navigation problem. In this study two input techniques were tested: remote control and speech input. The results showed that speech input was more effective as steps to complete tasks were less and shortcuts were used more often in the speech condition. However, the subjective data showed that the subjects were more satisfied with the remote control input. In conclusion, we recommend multimodal interaction where of speech input to complement the remote control unit. 1.