Applications built in a strongly decoupled, event-based interaction style have many commendable characteristics, including ease of dynamic configuration, accommodation of platform heterogeneity, and ease of distribution over a network. It is not always easy, however, to humanly grasp the dynamic behavior of such applications, since many threads are active and events are asynchronously transmitted. With the growing complexity of industrial use case requirements, independent and isolated triggers cannot fulfil the demands anymore. Fortunately, an independent trigger can be triggered by the result produced by other triggered actions and enables the modelling of complex use cases. The chains or graphs that consist of triggers, are called workflows. Therefore, workflow construction and manipulation become a must for implementing the complex use cases. This study presents an approach that aids in the discovery and visualization of the behaviors of event-based applications. It applies to real, implemented systems, without requiring the presence of component source code, and supports partial or incomplete, heuristic behavior specifcations. A prototype implementation of this study approach, was applied to VISION Cloud, a computational storage system that executes small programs, called storlets, as independent computation units in the storage. Similar to the trigger mechanism in database systems, storlets are triggered by specific events and then execute computations. Consequently, one storlet can also be triggered by the result produced by other storlets, and that is called connections between storlets. Due to the growing complexity of use case requirements, an urgent demand is to have real-time storlet work ow management supported in VISION system. Furthermore, because of the existence of connections between storlets in VISION, problems such as, non-termination triggering and unexpected overwriting, appear as side-effects. The thesis is part of the European Project VISION Cloud and it was written in collaboration with Swedish Institute of Compute Science (SICS), a partner of the project.