Performance Prediction for Black-Box Components Using Reengineered Parametric Behaviour Models
Created by W.Langdon from
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- @InProceedings{Kuperberg:2008:CBSE,
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author = "Michael Kuperberg and Klaus Krogmann and
Ralf Reussner",
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title = "Performance Prediction for Black-Box Components Using
Reengineered Parametric Behaviour Models",
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booktitle = "11th International Symposium on Component-Based
Software Engineering, CBSE 2008",
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year = "2008",
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editor = "Michel R. V. Chaudron and Clemens Szyperski and
Ralf Reussner",
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volume = "5282",
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series = "Lecture Notes in Computer Science",
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pages = "48--63",
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address = "Karlsruhe, Germany",
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month = oct # " 14-17",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, SBSE",
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isbn13 = "978-3-540-87890-2",
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DOI = "doi:10.1007/978-3-540-87891-9_4",
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size = "16 pages",
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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
parametrised 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.",
- }
Genetic Programming entries for
Michael Kuperberg
Klaus Krogmann
Ralf H Reussner
Citations