Generador de Valores de Casos de Prueba Funcionales

• Autores: Arloys Macías Rojas, Martha Dunia Delgado Dapena, Jenny Fajardo Calderín, Danay Larrosa Uribazo
• Localización: Lámpsakos, ISSN-e 2145-4086, ISSN 2145-4086, Nº. 15, 2016 (Ejemplar dedicado a: Edición 15: Prospectos de Ingeniería), págs. 51-58
• Idioma: español
• DOI: 10.21501/21454086.1767
• Títulos paralelos:
  • Generator of Values for Functional Test Cases
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    Diversos autores coinciden en la importancia de las pruebas como elemento de control de calidad del software y en la imposibilidad de realización de pruebas exhaustivas. Este criterio está sustentado en que la cantidad de escenarios y valores de prueba necesarios para lograr cobertura total es grande, lo que convierte el diseño de casos de prueba y en particular la generación de sus valores en un problema combinatorio.Este trabajo presenta una propuesta para la generación automática de valores de casos de prueba funcionales, mediante el uso de algoritmos metaheurísticos, maximizando la cobertura de los escenarios. Además, se detallan los algoritmos implementados para la generación de valores iniciales y para la generación de combinaciones. Adicionalmente se describen un conjunto de buenas prácticas para utilizar el componente y la comparación de los resultados obtenidos con otras soluciones existentes.

  • English

    Several authors agree with the importance of the tests like element of quality control of the software and in the impossibility of their realization of exhaustive way. This opinion defends that, the necessary quantity of stages and test values to achieve the maximum coverage is too big, what converts the test-case design, and in particular the generation of its values, in a combinatorial problem. That´s why, in many instances, in front of the impossibility of covering all the stages, testers leave out of the design some interesting values, which can discover inconsistencies with the specified requirements. This work presents a proposal for the automatic generation of values of functional test cases, by means of the use of meta-heuristic algorithms and maximizing the coverage of the stages. Furthermore, the algorithms implemented for the generation of initial values and for the generation of combinations are detailed. Additionally a set of good practices to use the component and the comparison of the obtained results with other existing solutions are described.

• Referencias bibliográficas
  • B. S. Ahmed, and K. Z. Zamli, “Comparison of metahuristic test generation strategies based on interaction elements coverage criterion,” en...
  • S. Anand, E. K. Burke, J. C. Tsong Yueh Chenc, M. B. Cohen, W. Grieskamp, M. Harman, M. J. Harrold, and P. McMinn, “An orchestrated survey...
  • F. Bouquet, C. Grandpierre, B. Legeard, and F. Peureux, "A test generation solution to automate software testing," en Proceedings...
  • J. C. Bregieiro, "Search-based test case generation for object-oriented java software using strongly-typed genetic programming," en...
  • E. Díaz, J. Tuya, R. Blanco, and J. J. Dolado, “A tabu search algorithm for structural software testing,” Computers & Operations Research,...
  • R. Ferguson, and B. Korel, “The chaining approach for software test data generation,” ACM Transactions on Software Engineering and Methodology...
  • M. Harman, “Automated test data generation using search based software engineering,” en Second International Workshop on Automation of Software...
  • M. Harman, S. A. Mansouri, and Y. Zhang, “Search-based software engineering: Trends, techniques and applications,” ACM Computing Surveys (CSUR),...
  • M. Z. Iqbal, A. Arcuri, and L. Briand, "Empirical investigation of search algorithms for environment model-based testing of real-time...
  • L. C. Lanzarini, and P. E. Battaiotto, “Dynamic generation of test cases with metaheuristics,” Journal of Computer Science & Technology...
  • A. M. Memon, M. E. Pollack, and M. L. Soffa, “Hierarchical GUI test case generation using automated planning,” IEEE Transactions on Software...
  • C. C. Michael, and G. McGraw, “Generating software test data by evolution,” IEEE Transactions on Software Engineering, Vol. 27, No. 12, pp....
  • G. J. Myers, T. Badgett, and C. Sandler, The art of software testing, 3a. ed., New Jersey, USA: JohnWiley & Sons, 2011. ISBN: 978-1-118-03196-4....
  • R. P. Pargas, M. J. Harrold, and R. R. Peck, “Test-data generation using genetic algorithms,” Journal of Software Testing, Verification and...
  • B. Pérez, and M. Polo, “Generación automática de casos de prueba para Líneas de Producto de Software,” REICIS. Revista Española de Innovación,...
  • R. S. Pressman, Ingeniería del Software: Un enfoque práctico, 7a. ed., México D.F.: McGraw-Hill, 2010. ISBN: 978-607-15-0314-5. [Online] Disponible...
  • A. Sakti, Y.-G. Guéhéneuc, and G. Pesant, "Boosting search based testing by using constraint based testing," Search Based Software...
  • S. Varshney, and M. Mehrotra, “Search based software test data generation for structural testing: a perspective,” ACM SIGSOFT Software Engineering...
  • J. Wegener, A. Baresel, and H. Sthamer, “Evolutionary test environment for automatic structural testing,” Information and Software Technology,...