Debugging is a fundamental tool for software developers, it is therefore included in the majority of modern integrated development environments available today. When the capabilities of such debuggers are to be implemented in a debugging tool for a clustered, real-time stream processing system, the task becomes very complex. Knowledge on how to build debuggers for such systems is missing, and there is a need for these types of tools in the emerging real-time data stream processing industry.

This thesis explores ways to implement and find usages of a debugging tool in a clustered, real-time processing environment. In previous research two papers were of particular interest as to form a basis for this thesis. However, these papers do not target real-time stream processing systems, so the knowledge gap still persists. It was found that these types of systems have extended requirements in addition to the functionality debuggers of today that has to be fulfilled.

The first requirement found was that shared states has to be represented in some way in the tool, and multiple solutions were proposed. The second problem found was that the real-time data stream had to be integrated into the tool in one or more ways. This thesis has brought up two ways to solve it; stream generation and stream sampling. The last problem brought up came from the need for users to be able to debug fatal bugs that has crashed the system. Three solutions were proposed, and the concluded Monte Carlo solution builds upon the previous two problems.

The thesis presents a special debugging protocol and a blueprintof a debugging tool, with implementation details included, forothers to take inspiration from. Thus it fills in the missingknowledge gap and successfully achieves the goal of answering thequestion of how to implement a debugging tool for a clustered,real-time data stream processing system.