Abstract
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.
This work is supported by the German Research Foundation (DFG), grant GRK 1076/1.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Rohr, M., van Hoorn, A., Giesecke, S., Matevska, J., Hasselbring, W.: Trace-context sensitive performance models from monitoring data of software-intensive systems. In: Workshop on Tools Infrastructures and Methodologies for the Evaluation of Research Systems (TIMERS 2008) at IEEE International Symposium on Performance Analysis of Systems and Software (April 2008)
Hamou-Lhadj, A., Lethbridge, T.C.: A survey of trace exploration tools and techniques. In: Conference of the Centre for Advanced Studies on Collaborative research CASCON 2004, pp. 42–55. IBM Press (2004)
Jain, R.: The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, 1st edn. John Wiley & Sons, Chichester (1991)
Bulej, L., Kalibera, T., Tůma, P.: Repeated results analysis for middleware regression benchmarking. Performance Evaluation 60(1-4), 345–358 (2005)
Arlitt, M.F., Krishnamurthy, D., Rolia, J.: Characterizing the scalability of a large web-based shopping system. ACM Transactions on Internet Technology 1(1), 44–69 (2001)
Ammons, G., Ball, T., Larus, J.R.: Exploiting hardware performance counters with flow and context sensitive profiling. In: Conference on Programming Language Design and Implementation (PLDI 1997), pp. 85–96. ACM, New York (1997)
Graham, S.L., Kessler, P.B., McKusick, M.K.: gprof: a call graph execution profiler. SIGPLAN Notes 17(6), 120–126 (1982)
Object Management Group (OMG): Unified Modeling Language: Superstructure Version 2.1.1 (February 2007)
Barrett, J.P., Goldsmith, L.: When is n sufficiently large? The American Statistician 30(2), 67–70 (1976)
Mielke, A.: Elements for response-time statistics in ERP transaction systems. Performance Evaluation 63(7), 635–653 (2006)
Rohr, M., van Hoorn, A., Matevska, J., Sommer, N., Stoever, L., Giesecke, S., Hasselbring, W.: Kieker: Continuous monitoring and on demand visualization of Java software behavior. In: IASTED International Conference on Software Engineering 2008, pp. 80–85. ACTA Press (February 2008)
van Hoorn, A., Rohr, M., Hasselbring, W.: Generating probabilistic and intensity-varying workload for web-based software systems. In: SPEC International Performance Evaluation Workshop (SIPEW 2008). LNCS, vol. 5119. Springer, Heidelberg (2008)
Montgomery, D.C., Runger, G.C.: Applied Statistics and Probability for Engineers, 3rd edn. John Wiley & Sons, Inc., Chichester (2003)
Duzbayev, N., Poernomo, I.: Runtime prediction of queued behaviour. In: Hofmeister, C., Crnković, I., Reussner, R. (eds.) QoSA 2006. LNCS, vol. 4214, pp. 78–94. Springer, Heidelberg (2006)
Diaconescu, A., Mos, A., Murphy, J.: Automatic performance management in component based software systems. In: First International Conference on Autonomic Computing (ICAC 2004), pp. 214–221. IEEE, Los Alamitos (2004)
Agarwal, M.K., Appleby, K., Gupta, M., Kar, G., Neogi, A., Sailer, A.: Problem determination using dependency graphs and run-time behavior models. In: Sahai, A., Wu, F. (eds.) DSOM 2004. LNCS, vol. 3278, pp. 171–182. Springer, Heidelberg (2004)
Govindraj, K., Narayanan, S., Thomas, B., Nair, P., P, S.: On using AOP for Application Performance Management. In: AOSD 2006 - Industry Track Proceedings (Technical Report IAI-TR-2006-3, University of Bonn), pp. 18–30 (March 2006)
Briand, L.C., Labiche, Y., Leduc, J.: Toward the reverse engineering of UML sequence diagrams for distributed Java software. IEEE Transactions on Software Engineering 32(9), 642–663 (2006)
Koziolek, H., Becker, S., Happe, J.: Predicting the Performance of Component-based Software Architectures with different Usage Profiles. In: 3rd International Conference on the Quality of Software Architectures (QoSA 2007). LNCS, vol. 4880, pp. 145–163. Springer, Heidelberg (2008)
Rohr, M., Giesecke, S., Hasselbring, W.: Timing Behavior Anomaly Detection in Enterprise Information Systems. In: 9th International Conference on Enterprise Information Systems (ICEIS 2007), June 2007, pp. 494–497. INSTICC Press (2007)
Xie, T., Notkin, D.: An empirical study of Java dynamic call graph extractors. Technical Report UW-CSE-02-12-03, University of Washington Department of Computer Science and Engineering, Seattle, WA, USA (December 2002)
Hamou-Lhadj, A.: Techniques to Simplify the Analysis of Execution Traces for Program Comprehension. PhD thesis, Ottawa-Carleton Institute for Computer Science, School of Information Technology and Engineering (SITE), University of Ottawa (2005)
Barham, P., Isaacs, R., Mortier, R., Narayanan, D.: Magpie: online modelling and performance-aware systems. In: 9th Conference on Hot Topics in Operating Systems (HOTOS 2003), USENIX Association, p. 15 (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rohr, M., van Hoorn, A., Giesecke, S., Matevska, J., Hasselbring, W., Alekseev, S. (2008). Trace-Context Sensitive Performance Profiling for Enterprise Software Applications. In: Kounev, S., Gorton, I., Sachs, K. (eds) Performance Evaluation: Metrics, Models and Benchmarks. SIPEW 2008. Lecture Notes in Computer Science, vol 5119. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69814-2_18
Download citation
DOI: https://doi.org/10.1007/978-3-540-69814-2_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69813-5
Online ISBN: 978-3-540-69814-2
eBook Packages: Computer ScienceComputer Science (R0)