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. Furthermore, events such as performance anomalies can often only be understood in correlation with the states of the applications. Therefore, an efficient and effective way to comprehend such software landscapes in combination with the details of each application is required. In this thesis, we introduce a live trace visualization approach to support system and program comprehension in large software landscapes. It features two perspectives: a landscape-level perspective using UML elements and an application-level perspective following the 3D software city metaphor. Our main contributions are 1) an approach named ExplorViz for enabling live trace visualization of large software landscapes, 2) a monitoring and analysis approach capable of logging and processing the huge amount of conducted method calls in large software landscapes, and 3) display and interaction concepts for the software city metaphor beyond classical 2D displays and 2D pointing devices. Extensive lab experiments show that our monitoring and analysis approach elastically scales to large software landscapes while imposing only a low overhead on the productive systems. Furthermore, several controlled experiments demonstrate an increased efficiency and effectiveness for solving comprehension tasks when using our visualization. ExplorViz is available as open-source software on www.explorviz.net. Additionally, we provide extensive experimental packages of our evaluations to facilitate the verifiability and reproducibility of our results.

Florian Fittkau received the BSc and MSc degrees in computer science from the Kiel University. Afterwards, he has been a Ph.D. student and researcher with the Software Engineering Group at Kiel University where he has worked on the presented ExplorViz approach. His research interests include software visualization, HCI, cloud computing, and empirical methods.