Integrated modeling tool for indexing and analyzing state machine trace

It is important to model and understand an application or system runtime behavior to identify potential performance problems. Execution tracing, the basis of various dynamic analysis methods includes the collection of events, metrics, and statistics about the runtime behaviors of systems and applications. However, comprehensive execution tracing can result in very large trace files, most of which are irrelevant to the problem at hand. This is compounded by the inflexibility and complexity of common tools in how the user specifies what to capture, making the collection of relevant statistics difficult. While existing solutions allow for an adaptive collection of metrics and statistics, they often require users to write large and complex scripts in a domain-specific language. In this paper, we propose a state machine based modeling tool that simplifies the creation of user-defined and data-driven trace-based analyses. The proposed method combines advanced kernel-space and user-space execution trace events with powerful and adaptable modeling in order to automatically generating event-based analysis based on users’ specific requirements and problems. The difficulty and complexity of user-defined event tracing is drastically reduced. We demonstrate the efficiency, effectiveness, and simplicity of our proposed tool through real use cases of multi-level dynamic execution tracing in the Linux kernel.