Trace-context sensitive performance profiling for enterprise software applications

Rohr, Matthias, van Hoorn, André, Giesecke, Simon, Matevska, Jasminka, Hasselbring, Wilhelm and Alekseev, Sergej (2008) Trace-context sensitive performance profiling for enterprise software applications [Paper] In: SPEC International Performance Evaluation Workshop (SIPEW '08), June 27--28, 2008, Darmstadt, Germany.

RohrvanHoornGieseckeMatevskaHasselbringAlekseev2008TraceContextSensitivePerformanceProfilingForEnterpriseSoftwareApplications-CameraReady-stamped-finalPageNumbers.pdf - Accepted Version

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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.

Document Type: Conference or Workshop Item (Paper)
Research affiliation: Kiel University > Software Engineering
Projects: Kieker
Date Deposited: 18 Feb 2012 06:05
Last Modified: 14 Jan 2016 11:34

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