Signal Generation for Search-Based Testing of Continuous Systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Windisch:2009:SBST,
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author = "Andreas Windisch and Noura {Al Moubayed}",
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title = "Signal Generation for Search-Based Testing of
Continuous Systems",
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booktitle = "2nd International Workshop on Search-Based Software
Testing",
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year = "2009",
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editor = "Phil McMinn and Robert Feldt",
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address = "Denver, Colorado, USA",
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month = "1 " # apr,
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organisation = "EvoTest",
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keywords = "genetic algorithms, genetic programming, linear
genetic programming, PSO, SBSE",
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URL = "http://iaser.tek.bth.se/feldt/conferences/sbst09/papers/windisch_sbst09.pdf",
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size = "10 pages",
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abstract = "Test case generation constitutes a critical activity
in software testing that is cost-intensive,
time-consuming and error-prone when done manually.
Hence, an automation of this process is required. One
automation approach is search-based testing for which
the task of generating test data is transformed into an
optimization problem which is solved using
metaheuristic search techniques. However, only little
work has been done so far applying search-based testing
techniques to systems that depend on continuous input
signals.
This paper proposes two novel approaches to generating
input signals from within search-based testing
techniques for continuous systems. These approaches are
then shown to be very effective when experimentally
applied to the problem of approximating a set of
realistic signals.",
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notes = "Fourier analysis (optimised by PSO) or GP combination
of sine, spline, linear, step and impulse. Multiple
chromosomes per individual. Homologous crossover, two
point crossover. Reducing mutation: removes genes from
chromosomes (cf also extending mutation: add genes to
end of chromosome). Multi-point mutation. Reinsertion:
add mutants to population. 6 training data from
Mercedes Benz cars, logged by CAN bus 30secs at
1khz.
sec 3.3 {"}small impulse-like steps do not carry much
weight{"}. Fourier series unable to reproduce constant
(wrong parameters chosen?). {"}slight advantage for the
linear genetic programming approach{"}. EvoTest.
http://iaser.tek.bth.se/feldt/conferences/sbst09 In
conjunction with ICST 2009 IEEE International
Conference on Testing, Verification and Validation",
- }
Genetic Programming entries for
Andreas Windisch
Noura Al Moubayed
Citations