Have a personal or library account? Click to login
Benefits of an Application of Evolutionary Strategy in the Process of Test Data Generation Cover

Benefits of an Application of Evolutionary Strategy in the Process of Test Data Generation

Management Systems in Production Engineering
Volume 22 (2016): Issue 2 (June 2016)
By: Marek Żukowicz  
Open Access
|Mar 2018

References

  1. [1] S.G. Ahmed. Automatic generation of basis test paths using variable length genetic algorithm, Journal Information Processing Letters, Volume 114 Issue 6, June, 2014, pp. 304-316.10.1016/j.ipl.2014.01.009
    Search in Google ScholarBack to article
  2. [2] R. Alavi, S. Lofti. The New Approach for Software Testing Using a Genetic Algorithm Based on Clustering Initial Test Instances, International Conference on Computer and Software Modeling 2011, IPCSIT vol.14 (2011).
    Search in Google ScholarBack to article
  3. [3] E. Alba, F. Chicano. Observations in using parallel and sequential evolutionary algorithms for automatic software testing, Computers & Operations Research, Vol. 35 Issue 10, October 2008, pp. 3163-3183.10.1016/j.cor.2007.01.016
    Search in Google ScholarBack to article
  4. [4] A. Aleti, L. Grunske. Test data generation with a Kalman filter-based adaptive genetic algorithm, The Journal of Systems and Software Vol. 103, May 2015 pp. 343-352.10.1016/j.jss.2014.11.035
    Search in Google ScholarBack to article
  5. [5] M. Alshraideh, B.A. Mahafzah, S. Al-Sharaeh. A multiple- population genetic algorithm for branch coverage test data generation, Software Quality Journal, Vol. 19, Volume 19, Issue 3 September 2011, pp. 489-513.10.1007/s11219-010-9117-4
    Search in Google ScholarBack to article
  6. [6] D. Farley, J. Humble. Ciągłe dostarczanie oprogramowania, Helion 2015.
    Search in Google ScholarBack to article
  7. [7] D. Gong, T. Tian, X. Yao. Grouping target paths for evolutionary generation of test data in paralel, The Journal of Systems and Software, Vol. 85, Issue 11, November 2012, pp. 2531-2540.10.1016/j.jss.2012.05.071
    Search in Google ScholarBack to article
  8. [8] D. Gong, Y. Zhang. Generating test data for both path coverage and fault detection using genetic algorithms, Frontiers of Computer Science, December 2013, Vol. 7, Issue 6, pp. 822-837.10.1007/s11704-013-3024-3
    Search in Google ScholarBack to article
  9. [9] D. Gong, Y. Zhang. Generating test data for both path coverage and fault detection using genetic algorithms: multi-path case, Frontiers of Computer Science, October 2014, Vol. 8, Issue 5, pp. 726-740.10.1007/s11704-014-3372-7
    Search in Google ScholarBack to article
  10. [10] M.J. Harrold, R. Pargas, R. R. Peck. Test-Data generation using genetics algorithms, Journal of Software Testing, Verification and Reliability 1999.
    Search in Google ScholarBack to article
  11. [11] I. Hermadi, C. Lokan, R. Sarker. Dynamic stopping criteria for search-based test data generation for path testing , Information and Software Technology, April 2014 Vol. 56, pp. 395-407.10.1016/j.infsof.2014.01.001
    Search in Google ScholarBack to article
  12. [12] J. Hudec, E. Gramatova. An Efficient functional test generation method for processors using genetic algorithms, Journal of Electrical Engineering, July 2015, Vol. 66, Issue. 4, pp. 186-193.10.2478/jee-2015-0031
    Search in Google ScholarBack to article
  13. [13] N. Khurana, R.S. Chillar. Test Case Generation and Optimization using UML Models and Genetic Algorithm, Procedia Computer Science, August 2015, Vol. 57, pp. 966-1004.10.1016/j.procs.2015.07.502
    Search in Google ScholarBack to article
  14. [14] H. Kim, P.R. Srivastava. Application of Genetic Algorithm in Software Testing, International Journal of Software Engineering and Its Applications, October 2009, Vol. 3, Issue 4, pp. 87-96.
    Search in Google ScholarBack to article
  15. [15] R. Krishnamoorthi, A. Sahaaya, S.A. Mary. Regression Test Suite Prioritization using Genetic Algorithms, International Journal of Hybrid Information Technology, July 2009 Vol.2, Issue .3, July.
    Search in Google ScholarBack to article
  16. [16] C. Mao. Harmony search-based test data generation for branch coverage in software structural testing, Neural Computing and Applications, September 2013, Vol. 25, Issue 1, pp.199-216. Springer-Verlag London 2013.10.1007/s00521-013-1474-z
    Search in Google ScholarBack to article
  17. [17] M. Mirzaaghaei, F. Pastore, M. Pezze. Automatic test case evolution, Software testing, Verification and Reliability, April 2014, Vol. 24, Issue 5, pp.386-411.10.1002/stvr.1527
    Search in Google ScholarBack to article
  18. [18] A. Piaskowy, R. Smilgin. Dane Testowe, teoria i praktyka, Helion 2011.
    Search in Google ScholarBack to article
  19. [19] A. Roman, Testowanie i jakość oprogramowania, PWN 2015.
    Search in Google ScholarBack to article
  20. [20] D. Rutkowska, M. Piliński, L. Rutkowski. Sieci neuronowe, algorytmy genetyczne i systemy rozmyte, PWN Wwa 1997.
    Search in Google ScholarBack to article
  21. [21] D. Warchoł, M. Żukowicz. Testing education: test case prioritization using matrices, General and Professional Education, May 2015, Vol. 1, Issue 8, pp. 57-62.
    Search in Google ScholarBack to article
  22. [22] M. Żukowicz. Edukacja testowania: Narzędzie All-pairs Testing w procesie optymalizacji testów konfiguracji - zastosowanie narzędzia w systemie B2B OPTIbud, General and Professional Education, Dezember 2015, Vol. 4, Issue 12, pp. 99-106.
    Search in Google ScholarBack to article
  23. [23] M. Żukowicz. Edukacyjne i ekonomiczne aspekty zastosowania cyklu Hamiltona w projektowaniu i testowaniu oprogramowania, General and Professional Education, numer Dezember 2014, Vol. 4, Issue 13, pp. 95-102.
    Search in Google ScholarBack to article
  24. [24] M. Żukowicz, O pewnych problemach analizy wartości brzegowych, Internet:, http://testerzy.pl/materialy/index.php?file=analiza-wartosci-brzegowych.pdf, access date 03.03.2016.
    Search in Google ScholarBack to article
DOI: https://doi.org/10.2478/mspe-06-02-2016 | Journal eISSN: 2450-5781 | Journal ISSN: 2299-0461
Journal RSS Feed
Language: English
Page range: 106 - 109
Submitted on: Feb 1, 2016
Accepted on: Apr 1, 2016
Published on: Mar 15, 2018
Published by: STE Group sp. z.o.o.
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
evolutionary strategies,
test data,
test data quality criteria,
optimization test data
Related subjects:
Business and economics,
Business management,
Management accounting, financial controlling, cost calculation, investment,
Engineering,
Mechanical engineering,
Production technology,
Tools and methods,
Process engineering and industrial engineering

© 2018 Marek Żukowicz, published by STE Group sp. z.o.o.
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Previous articleVolume 22 (2016): Issue 2 (June 2016)Next article