Abstract
In component-based software engineering, the response time of an entire application is often predicted from the execution durations of individual component services. However, these execution durations are specific for an execution platform (i.e. its resources such as CPU) and for a usage profile. Reusing an existing component on different execution platforms up to now required repeated measurements of the concerned components for each relevant combination of execution platform and usage profile, leading to high effort. This paper presents a novel integrated approach that overcomes these limitations by reconstructing behaviour models with platform-independent resource demands of bytecode components. The reconstructed models are parameterised over input parameter values. Using platform-specific results of bytecode benchmarking, our approach is able to translate the platform-independent resource demands into predictions for execution durations on a certain platform. We validate our approach by predicting the performance of a file sharing application.
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References
Albert, E., Arenas, P., Genaim, S., Puebla, G., Zanardini, D.: Experiments in Cost Analysis of Java Bytecode. Electr. Notes Theor. Comput. Sci. 190(1), 67–83 (2007)
Becker, S., Happe, J., Koziolek, H.: Putting Components into Context - Supporting QoS-Predictions with an explicit Context Model. In: Reussner, R., Szyperski, C., Weck, W. (eds.) WCOP 2006 (June 2006)
Becker, S., Koziolek, H., Reussner, R.: The Palladio Component Model for Model-Driven Performance Prediction. Journal of Systems and Software (in press, 2008) (accepted manuscript)
Bertolino, A., Mirandola, R.: CB-SPE Tool: Putting Component-Based Performance Engineering into Practice. In: Crnkovic, I., Stafford, J.A., Schmidt, H.W., Wallnau, K.C. (eds.) CBSE 2004. LNCS, vol. 3054, pp. 233–248. Springer, Heidelberg (2004)
Binder, W., Hulaas, J.: Flexible and Efficient Measurement of Dynamic Bytecode Metrics. In: GPCE 2006, pp. 171–180. ACM, New York (2006)
Binder, W., Hulaas, J.: Using Bytecode Instruction Counting as Portable CPU Consumption Metric. Electr. Notes Theor. Comput. Sci. 153(2), 57–77 (2006)
Bondarev, E., de With, P., Chaudron, M., Musken, J.: Modelling of Input- Parameter Dependency for Performance Predictions of Component-Based Embedded Systems. In: Proceedings of the 31th EUROMICRO Conference (EUROMICRO 2005) (2005)
Bruneton, E., Lenglet, R., Coupaye, T.: ASM: a code manipulation tool to implement adaptable systems. Adaptable and Extensible Component Systems (2002)
Courtois, M., Woodside, C.M.: Using regression splines for software performance analysis. In: WOSP 2000, Ottawa, Canada, September 2000, pp. 105–114. ACM, New York (2000)
Donnell, J.: Java Performance Profiling using the VTune Performance Analyzer (Retrieved 2007-01-18) (2004)
Ernst, M.D., et al.: The Daikon system for dynamic detection of likely invariants. Science of Computer Programming 69(1-3), 35–45 (2007)
Harman, M.: The Current State and Future of Search Based Software Engineering. In: Future of Software Engineering, 2007. FOSE 2007, May 23-25, 2007, pp. 342–357 (2007)
Herder, C., Dujmovic, J.J.: Frequency Analysis and Timing of Java Bytecodes. Technical report, Computer Science Department, San Francisco State University, Technical Report SFSU-CS-TR-00.02 (2000)
Hrischuk, C.E., Murray Woodside, C., Rolia, J.A.: Trace-based load characterization for generating performance software models. IEEE Transactions Software Engineering 25(1), 122–135 (1999)
Hu, E.Y.-S., Wellings, A.J., Bernat, G.: Deriving Java Virtual Machine Timing Models for PortableWorst-Case Execution Time Analysis. In: Meersman, R., Tari, Z. (eds.) OTM-WS 2003. LNCS, vol. 2889, pp. 411–424. Springer, Heidelberg (2003)
Israr, T., Woodside, M., Franks, G.: Interaction tree algorithms to extract effective architecture and layered performance models from traces. Journal of Systems and Software, 5th International Workshop on Software and Performance 80(4), 474–492 (2007)
Koza, J.R.: Genetic Programming – On the Programming of Computers by Means of Natural Selection, 3rd edn. MIT Press, Cambridge (1993)
Kuperberg, M., Becker, S.: Predicting Software Component Performance: On the Relevance of Parameters for Benchmarking Bytecode and APIs. In: Reussner, R., Czyperski, C., Weck, W. (eds.) WCOP 2007 (July 2007)
Kuperberg, M., Krogmann, M., Reussner, R.: ByCounter: Portable Runtime Counting of Bytecode Instructions and Method Invocations. In: BYTECODE 2008 (2008)
Lambert, J., Power, J.F.: Platform Independent Timing of Java Virtual Machine Bytecode Instructions. In: Workshop on Quantitative Aspects of Programming Languages, Budapest, Hungary, March 29-30 (2008)
McMinn, P.: Search-based software test data generation: a survey. Software Testing, Verification and Reliability 14(2), 105–156 (2004)
Meffert, K.: JGAP - Java Genetic Algorithms Package (last retrieved: 2008-03-18), http://jgap.sourceforge.net/
Meyerhöfer, M., Meyer-Wegener, K.: Estimating Non-functional Properties of Component-based Software Based on Resource Consumption. Electr. Notes Theor. Comput. Sci. 114, 25–45 (2005)
Smith, C.U., Williams, L.G.: Performance Engineering Evaluation of Object- Oriented Systems with SPEED. In: Marie, R., Plateau, B., Calzarossa, M.C., Rubino, G.J. (eds.) TOOLS 1997. LNCS, vol. 1245, Springer, Heidelberg (1997)
Zhang, X., Seltzer, M.: HBench:Java: an application-specific benchmarking framework for Java virtual machines. In: JAVA 2000: Proceedings of the ACM 2000 conference on Java Grande, pp. 62–70. ACM Press, New York (2000)
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Kuperberg, M., Krogmann, K., Reussner, R. (2008). Performance Prediction for Black-Box Components Using Reengineered Parametric Behaviour Models. In: Chaudron, M.R.V., Szyperski, C., Reussner, R. (eds) Component-Based Software Engineering. CBSE 2008. Lecture Notes in Computer Science, vol 5282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87891-9_4
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DOI: https://doi.org/10.1007/978-3-540-87891-9_4
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