Article

A case study on the use of genetic algorithms to generate test cases for temporal systems

Authors:

Karnig Derderian,

Mercedes G. Merayo,

Robert M. Hierons,

Manuel NúñezAuthors Info & Claims

IWANN'11: Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II

Pages 396 - 403

Published: 08 June 2011 Publication History

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Abstract

Generating test data for formal state based specifications is computationally expensive. In previous work we presented a framework that addressed this issue by representing the test data generation problem as an optimisation problem. In this paper we analyze a communications protocol to illustrate how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs show to outperform random search and seem to scale well as the problem size increases. We consider a very simple fitness function that can be used with other evolutionary search techniques and automated test case generation suites.

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Cited By

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Rodrigues DDelamaro MCorrêa CNunes F(2018)Using Genetic Algorithms in Test Data GenerationACM Computing Surveys10.1145/318265951:2(1-23)Online publication date: 22-May-2018
https://dl.acm.org/doi/10.1145/3182659
Núñez M(2011)Formal testing of timed and probabilistic systemsProceedings of the 23rd IFIP WG 6.1 international conference on Testing software and systems10.5555/2075545.2075547(9-14)Online publication date: 7-Nov-2011
https://dl.acm.org/doi/10.5555/2075545.2075547

A case study on the use of genetic algorithms to generate test cases for temporal systems
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis

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Published In

IWANN'11: Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II

June 2011

684 pages

ISBN:9783642214974

Editors:
Joan Cabestany
Departament d'Enginyeria Electrònica, Universitat Politècnica de Catalunya, Barcelona, Spain
,
Ignacio Rojas
Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain
,
Gonzalo Joya
Universidad de Málaga, Departamento Tecnologia Electrónica, Málaga, Spain

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Springer-Verlag

Berlin, Heidelberg

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Published: 08 June 2011

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Rodrigues DDelamaro MCorrêa CNunes F(2018)Using Genetic Algorithms in Test Data GenerationACM Computing Surveys10.1145/318265951:2(1-23)Online publication date: 22-May-2018
https://dl.acm.org/doi/10.1145/3182659
Núñez M(2011)Formal testing of timed and probabilistic systemsProceedings of the 23rd IFIP WG 6.1 international conference on Testing software and systems10.5555/2075545.2075547(9-14)Online publication date: 7-Nov-2011
https://dl.acm.org/doi/10.5555/2075545.2075547

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Complete IOCO test cases: a case study

A new approach to generate and optimize test cases for UML state diagram using genetic algorithm: http://doi.acm.org/10.1145/180921.2180933

Using genetic algorithms to generate test sequences for complex timed systems

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