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  • Testing of multi-threaded programs isa~demanding work due to the many possible thread interleavings one shouldexamine. The noise injection technique helps to increase the number of threadinterleavings examined during repeated test executions provided that a~suitablesetting of noise injection heuristics is used. The problem of finding sucha~setting, i.e., the so called test and noise configuration search problem (TNCSproblem), is not easy to solve. In this paper, we show how to applya~multi-objective genetic algorithm (MOGA) to the TNCS problem. In particular,we focus on generation of TNCS solutions that cover a~high number of distinctinterleavings (especially those which are rare) and provide stable results atthe same time. To achieve this goal, we study suitable metrics and ways how tosuppress effects of non-deterministic thread scheduling on the proposedMOGA-based approach. We also discuss a~choice of a~concrete MOGA and itsparameters suitable for our setting. Finally, we show on a~set o
  • Testing of multi-threaded programs isa~demanding work due to the many possible thread interleavings one shouldexamine. The noise injection technique helps to increase the number of threadinterleavings examined during repeated test executions provided that a~suitablesetting of noise injection heuristics is used. The problem of finding sucha~setting, i.e., the so called test and noise configuration search problem (TNCSproblem), is not easy to solve. In this paper, we show how to applya~multi-objective genetic algorithm (MOGA) to the TNCS problem. In particular,we focus on generation of TNCS solutions that cover a~high number of distinctinterleavings (especially those which are rare) and provide stable results atthe same time. To achieve this goal, we study suitable metrics and ways how tosuppress effects of non-deterministic thread scheduling on the proposedMOGA-based approach. We also discuss a~choice of a~concrete MOGA and itsparameters suitable for our setting. Finally, we show on a~set o (en)
Title
  • Multi-objective Genetic Optimization for Noise-Based Testing of Concurrent Software
  • Multi-objective Genetic Optimization for Noise-Based Testing of Concurrent Software (en)
skos:prefLabel
  • Multi-objective Genetic Optimization for Noise-Based Testing of Concurrent Software
  • Multi-objective Genetic Optimization for Noise-Based Testing of Concurrent Software (en)
skos:notation
  • RIV/00216305:26230/14:PU112027!RIV15-MSM-26230___
http://linked.open...avai/riv/aktivita
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  • P(ED1.1.00/02.0070), P(LH13265), S
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  • 31061
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  • RIV/00216305:26230/14:PU112027
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  • Concurrent programs, testing, noise injection, genetic algorithm, multi-objective (en)
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  • [96721CECBB91]
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  • Fortaleza, Aquiraz, Ceará, Brasil
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  • Heidelberg
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  • SSBSE'14
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  • Hrubá, Vendula
  • Křena, Bohuslav
  • Letko, Zdeněk
  • Vojnar, Tomáš
  • Pluháčková, Hana
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  • Springer-Verlag
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  • 978-3-319-09939-2
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  • 26230
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