Context: The number of software applications deployed in organizations is constantly increasing. Those applications – often several hundreds – form large software landscapes. Objective: The comprehension of such landscapes and their applications is often impeded by, for instance, architectural erosion, personnel turnover, or changing requirements. Therefore, an efficient and effective way to comprehend such software landscapes is required. Method: In our ExplorViz visualization, we introduce hierarchical abstractions aiming at solving system comprehension tasks fast and accurately for large software landscapes. Besides hierarchical visualization on the landscape level, ExplorViz provides multi-level visualization from the landscape to the level of individual applications. The 3D application-level visualization is empirically evaluated with a comparison to the Extravis approach, with physical models and in virtual reality. To evaluate ExplorViz, we conducted four controlled experiments. We provide packages containing all our experimental data to facilitate the verifiability, reproducibility, and further extensibility of our results. Results: We observed a statistical significant increase in task correctness of the hierarchical visualization compared to the flat visualization. The time spent did not show any significant differences. For the comparison with Extravis, we observed that solving program comprehension tasks using ExplorViz leads to a significant increase in correctness and in less or similar time spent. The physical models improved the team-based program comprehension process for specific tasks by initiating gesture-based interaction, but not for all tasks. The participants of our virtual reality experiment with ExplorViz rated the realized gestures for translation, rotation, and selection as highly usable. However, our zooming gesture was less favored. Conclusion: The results backup our claim that our hierarchical and multi-level approach enhances the current state of the art in landscape and application visualization for better software system comprehension, including new forms of interaction with physical models and virtual reality.

For efficient and effective program comprehension, it is essential to provide software engineers with appropriate visualizations of the program's execution traces. Empirical studies, such as controlled experiments, are required to assess the effectiveness and efficiency of proposed visualization techniques. We present controlled experiments to compare the trace visualization tools Extravis and Explor Viz in typical program comprehension tasks. We replicate the first controlled experiment with a second one targeting a differently sized software system. In addition to a thorough analysis of the strategies chosen by the participants, we report on common challenges comparing trace visualization techniques. Besides our own replication of the first experiment, we provide a package containing all our experimental data to facilitate the verifiability, reproducibility and further extensibility of our presented results. Although subjects spent similar time on program comprehension tasks with both tools for a small-sized system, analyzing a larger software system resulted in a significant efficiency advantage of 28 percent less time spent by using Explor Viz. Concerning the effectiveness (correct solutions for program comprehension tasks), we observed a significant improvement of correctness for both object system sizes of 39 and 61 percent with Explor Viz.

In many enterprises the number of deployed applications is constantly increasing. Those applications - often several hundreds - form large software landscapes. The comprehension of such landscapes is frequently impeded due to, for instance, architectural erosion, personnel turnover, or changing requirements. Therefore, an efficient and effective way to comprehend such software landscapes is required. The current state of the art often visualizes software landscapes via flat graph-based representations of nodes, applications, and their communication. In our ExplorViz visualization, we introduce hierarchical abstractions aiming at solving typical system comprehension tasks fast and accurately for large software landscapes. To evaluate our hierarchical approach, we conduct a controlled experiment comparing our hierarchical landscape visualization to a flat, state-of-the-art visualization. In addition, we thoroughly analyze the strategies employed by the participants and provide a package containing all our experimental data to facilitate the verifiability, reproducibility, and further extensibility of our results. We observed a statistically significant increase of 14 % in task correctness of the hierarchical visualization group compared to the flat visualization group in our experiment. The time spent on the system comprehension tasks did not show any significant differences. The results backup our claim that our hierarchical concept enhances the current state of the art in landscape visualization.

Building architects, but also civil or mechanical engineers often build from their designs physical 3D models for a better presentation, comprehension, and communication among stakeholders. Software engineers usually create visualizations of their software designs as digital objects to be presented on a screen only. 3D software visualization metaphors, such as the software city metaphor, provide a basis for exporting those on-screen software visualizations into physical models. This can be achieved by 3D-printers to transfer the advantages of real, physical, tangible architecture models from traditional engineering disciplines to software engineering. We present a new research perspective of using physical models to support software engineering. Furthermore, we describe four envisioned usage scenarios for physical models which provide a plethora of new research topics. To examine the benefits of our concept, we investigate the first usage scenario by evaluating the impact of using physical models on program comprehension in teams through a first controlled experiment. Since the usage of physical models had a diverging influence for our chosen task set, we report on the qualitative results in this paper. We observed that the physical models improved the team-based program comprehension process for specific tasks by initiating gesture-based interaction.

Software visualizations, such as the software city metaphor, are usually displayed on 2D screens and controlled by means of a mouse and thus often do not take advantage of more natural interaction techniques. Virtual reality (VR) approaches aim to improve the user experience. Emerging new technologies, like the Oculus Rift, dramatically enhance the VR experience at an affordable price. Therefore, new technologies have the potential to provide even higher immersion - and thus benefits - than previous VR approaches.

Migrating existing enterprise software to cloud platforms involves the comparison of competing cloud deployment options (CDOs). A CDO comprises a combination of a specific cloud environment, deployment architecture, and runtime reconfiguration rules for dynamic resource scaling. Our simulator CDOSim can evaluate CDOs, e.g., regarding response times and costs. However, the design space to be searched for well-suited solutions is extremely huge. In this paper, we approach this optimization problem with the novel genetic algorithm CDOXplorer. It uses techniques of the search-based software engineering field and CDOSim to assess the fitness of CDOs. An experimental evaluation that employs, among others, the cloud environments Amazon EC2 and Microsoft Windows Azure, shows that CDOXplorer can find solutions that surpass those of other state-of-the-art techniques by up to 60%. Our experiment code and data and an implementation of CDOXplorer are available as open source software.

The increasing code complexity in modern enterprise software systems exceeds the capabilities of most software engineers to understand the system's behavior by just looking at its program code. Large software landscapes, e.g., applications in a cloud infrastructure, further increase this complexity. A solution to these problems is visualizing the applications of the software landscape to ease program comprehension and to understand the respective communication. An established visualization concept is the 3D city metaphor. It utilizes the familiarity with navigating a city to improve program comprehension. Dynamic analysis, e.g., monitoring, can provide the required program traces of the communication. In this paper, we present our live visualization approach of monitoring traces for large software landscapes. It combines a landscape and a system level perspective. The landscape level perspective provides an overview of the software landscape utilizing the viewer's familiarity with UML. The system level perspective provides a visualization utilizing the city metaphor for each software system.

The increasing code complexity in modern software systems exceeds the capabilities of most software engineers to understand the system's behavior by just looking at its program code. The addition of concurrency issues through the advent of multi-core processors in the consumer market further escalates this complexity. A solution to these problems is visualizing a model of the system to ease program comprehension. Especially for the comprehension of concurrency issues, static information is often not sufficient. For this purpose, profiling and monitoring can provide additional information on the actual behavior of a system. An established visualization approach is the 3D city metaphor. It utilizes the familiarity with navigating a city to improve program comprehension. In this paper, we present our trace-based SynchroVis 3D visualization approach for concurrency. It employs the city metaphor to visualize both static and dynamic properties of software systems with a focus on illustrating the concurrent behavior. To evaluate our approach, we provide an open source implementation of our concepts and present an exemplary dining philosophers scenario showing its feasibility.