License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.08351.5
URN: urn:nbn:de:0030-drops-20118
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2009/2011/
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Windisch, Andreas

Ideas on Signal Generation for Evolutionary Testing of Continuous Systems

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08351.WindischAndreas.Paper.2011.pdf (0.1 MB)

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 so far been
done to apply search-based testing techniques to systems that depend on
continuous input signals rather than single discrete input values.
This paper proposes three novel approaches to generating input signals
from within search-based testing techniques for continuous systems.

BibTeX - Entry

@InProceedings{windisch:DagSemProc.08351.5,
  author =	{Windisch, Andreas},
  title =	{{Ideas on Signal Generation for Evolutionary Testing of Continuous Systems}},
  booktitle =	{Evolutionary Test Generation},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{8351},
  editor =	{Holger Schlingloff and Tanja E. J. Vos and Joachim Wegener},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2009/2011},
  URN =		{urn:nbn:de:0030-drops-20118},
  doi =		{10.4230/DagSemProc.08351.5},
  annote =	{Keywords: Search-Based Testing, Optimization, Metaheuristic}
}

Keywords: Search-Based Testing, Optimization, Metaheuristic
Collection: 08351 - Evolutionary Test Generation
Issue Date: 2009
Date of publication: 25.05.2009

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