Trace-Context Sensitive Performance Profiling for Enterprise Software Applications

Software response time distributions can be of high variance and multi-modal. Such characteristics reduce confidence or applicability in various statistical evaluations. We contribute an approach to correlating response times to their corresponding operation execution sequence. This provides calling-context sensitive timing behavior models. The approach is based on three equivalence relations: caller-context, stack-context, and trace-context equivalence. To prevent model size explosion, a tree-based hierarchy provides timing behavior models that provide a trade-off between timing behavior model size and the amount of calling-context information considered. In the case study, our approach provides response time distributions with significantly lower standard deviation, compared to using less or no calling-context information. An example from a performance analysis of an industry system demonstrates that multi-modal distributions can be replaced by multiple unimodal distributions using trace-context analysis.