An Integrated, Interactive and Multi-Objective Approach to the Problems of Selection, Prioritization and Allocation of Test Cases
Abstract
The test cases selection, prioritization and allocation problems can be considered difficult because of the large number of possible solutions that should be considered in solving these problems and the many factors that can influence the search for these solutions. There are several studies that use optimization techniques in the search for solutions to difficult problems of software engineering at the recent area of research known as Search-Based Software Engineering. In this context, this work proposes an integrated, interactive and multi-objective approach to the test cases selection, prioritization and allocation problems. Two experiments are detailed, showing the effectiveness of optimization techniques in the three problems.
Keywords:
Approach, Problems, Test Cases
References
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Li, Z., Harman, M., Hierons, R. M. (2007) “Search Algorithms for Regression Test Case Prioritization”, IEEE Transactions on Software Engineering, v. 33, n. 4, P. 225- 237.
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Maia, C. L. B. (2011) “Uma Abordagem Integrada, Interativa e Multi-Objetiva para os Problemas de Seleção, Priorização e Alocação de Casos de Teste”, Dissertação de Mestrado da Universidade Estadual do Ceará (UECE).
Nebro, A., Durillo, J., Coello, C. C., Luna, F, Alba, E. (2008) “A Study of Convergence Speed in Multi-Objective Metaheuristics”, Parallel Problem Solving from Nature, Springer, p. 763-772.
Nebro, A. J., Durillo, J. J., Luna, F., Dorronsoro, B., Alba, E. (2009) “MOCell: A cellular genetic algorithm for multiobjective optimization”, International Journal of Intelligent Systems, v. 24, n. 7, p. 726-746.
Walcott, K. R., Soffa, M. L., Kapfhammer, G. M., Roos, R. S. (2006) “Time-Aware Test Suite Prioritization”, In: Proceedings of the International Symposium on Software Testing and Analysis, p. 1-12.
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Zitzler, E., Deb, K, Thiele, L. (2000) “Comparison of Multiobjective Evolutionary Algorithms: Empirical Results”, Evolutionary Computation, v. 8, n. 2, p. 173-195.
Zitzler, E., Laumanns, M., Thiele (2001) “SPEA2: Improving the Strength Pareto Evolutionary Algorithm”.
Bagnall, A. J., Rayward-Smith, V. J., Whittley, I. M. (2001) “The Next Release Problem”, Information and Software Technology, Elsevier, v. 43, n. 14, p. 883-890.
Bastos, A., Cristalli, R., Moreira, T., Rios, E. (2007), Base de Conhecimento em Teste de Software, Martins Fontes, segunda edição.
Deb, K., Agrawal, S., Pratap, A., Meyarivan, T. (2002) “A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II”, In: Proceedings of the Parallel Problem Solving from Nature VI Conference, Springer, p. 849-858.
Deb, K. (2008), Multi-Objective Optimization using Evolutionary Algorithms, John Wiley & Sons, 1st Edition.
Di Penta, M., Harman, M., Antoniol, G., Qureshi, F. (2007) “The effect of communication overhead on software maintenance project staffing: a search-based approach”, IEEE International Conference on Software Maintenance, p. 315-324.
Di Penta, M., Harman, M., Antoniol, G. (2009) “The use of Search-Based Optimization Techniques to Schedule and Staff Software Projects: an Approach and an Empirical Study”, Software – Practice and Experience.
Holland, J. H. (1975), Adaptation in Natural and Artificial Systems, The University of Michigan Press.
Kuperberg, M., Omri, F. (2009) “Using Heuristics to Automate Parameter Generation for Benchmarking of Java Methods”, Electronic Notes in Theoretical Computer Science, v. 253, n. 1, p. 57-75.
Li, R., Chaudron, M. R. V., Ladan, R. C. (2009) “Towards Automated Software Architectures Design using Model Transformations and Evolutionary Algorithms”, In: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation (GECCO’10), p. 1333.
Li, Z., Harman, M., Hierons, R. M. (2007) “Search Algorithms for Regression Test Case Prioritization”, IEEE Transactions on Software Engineering, v. 33, n. 4, P. 225- 237.
Maia, C. L. B., Carmo, R. A. F., Freitas, F. G., Campos, G. A. L., Souza, J . T. (2009) “A Multi-Objective Approach for the Regression Test Case Selection Problem”, In: Proceedings of XLI Simpósio Brasileiro de Pesquisa Operacional, p. 1824-1835.
Maia, C. L. B. (2011) “Uma Abordagem Integrada, Interativa e Multi-Objetiva para os Problemas de Seleção, Priorização e Alocação de Casos de Teste”, Dissertação de Mestrado da Universidade Estadual do Ceará (UECE).
Nebro, A., Durillo, J., Coello, C. C., Luna, F, Alba, E. (2008) “A Study of Convergence Speed in Multi-Objective Metaheuristics”, Parallel Problem Solving from Nature, Springer, p. 763-772.
Nebro, A. J., Durillo, J. J., Luna, F., Dorronsoro, B., Alba, E. (2009) “MOCell: A cellular genetic algorithm for multiobjective optimization”, International Journal of Intelligent Systems, v. 24, n. 7, p. 726-746.
Walcott, K. R., Soffa, M. L., Kapfhammer, G. M., Roos, R. S. (2006) “Time-Aware Test Suite Prioritization”, In: Proceedings of the International Symposium on Software Testing and Analysis, p. 1-12.
Yoo, S., Harman, M. (2007) “Pareto Efficient Multi-Objective Test Case Selection”, In: Proceedings of International Symposium on Software Testing and Analysis (ISSTA'07), p. 140-150.
Zitzler, E., Deb, K, Thiele, L. (2000) “Comparison of Multiobjective Evolutionary Algorithms: Empirical Results”, Evolutionary Computation, v. 8, n. 2, p. 173-195.
Zitzler, E., Laumanns, M., Thiele (2001) “SPEA2: Improving the Strength Pareto Evolutionary Algorithm”.
Published
2012-07-11
How to Cite
MAIA, Camila Loiola Brito; DE SOUZA, Jerffeson Teixeira.
An Integrated, Interactive and Multi-Objective Approach to the Problems of Selection, Prioritization and Allocation of Test Cases. In: BRAZILIAN SOFTWARE QUALITY SYMPOSIUM (SBQS), 11. , 2012, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2012
.
p. 173-187.
DOI: https://doi.org/10.5753/sbqs.2012.15315.
