Get Automatic Generation of Combinatorial Test Data PDF

By Jian Zhang

ISBN-10: 3662434288

ISBN-13: 9783662434284

ISBN-10: 3662434296

ISBN-13: 9783662434291

This ebook reports the cutting-edge in combinatorial checking out, with specific emphasis at the computerized new release of try out facts. It describes the main standard techniques during this quarter - together with algebraic building, grasping equipment, evolutionary computation, constraint fixing and optimization - and explains significant algorithms with examples. additionally, the ebook lists a few attempt iteration instruments, in addition to benchmarks and functions. Addressing a multidisciplinary subject, will probably be of specific curiosity to researchers and pros within the parts of software program checking out, combinatorics, constraint fixing and evolutionary computation.

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Both of the two candidate test cases cover two uncovered target combinations. We choose (1, 1, 2, 2) as the fourth test case. Now we remove the target combinations covered by the fourth test case. So the set of uncovered target combinations now becomes: { /////////////////////////// (1,1,-,-), /////////////////////////// (1,-,1,-), /////////////////////////// (1,-,-,1), /////////////////////////// (-,1,1,-), /////////////////////////// (-,1,-,1), /////////////////////////// (-,-,1,1), /////////////////////////// (1,2,-,-), /////////////////////////// (1,-,2,-), /////////////////////////// (1,-,-,2), /////////////////////////// (-,1,2,-), /////////////////////////// (-,1,-,2), (-,-,1,2), ///////////////////////// (2,1,-,-) ///////////////////////// (2,-,1,-), ///////////////////////// (2,-,-,1), ///////////////////////// (-,2,1,-), ///////////////////////// (-,2,-,1), (-,-,2,1), ///////////////////////// (2,2,-,-), (2,-,2,-), (2,-,-,2), /////////////////////////// (-,2,2,-), /////////////////////////// (-,2,-,2), ///////////////////////// (-,-,2,2) }.

Constructing interaction test suites for highly-configurable systems in the presence of constraints: a greedy approach. IEEE Trans. Softw. Eng. 34(5), 633–650 (2008) 10. : Pairwise testing in the real world: practical extensions to test-case scenarios. In: Proceedings of the 24th Pacific Northwest Software Quality Conference (PNSQC’06), pp. 419–430 (2006) 11. : Automating test case generation for the new generation mission software system. In: Proceedings of the IEEE Aerospace Conference, vol.

In: Proceedings of the Sixth International Conference on Software Testing, Verification and Validation (ICST’13), IEEE, pp. 242–251 (2013) Chapter 5 Evolutionary Computation and Metaheuristics Abstract This chapter describes how to use metaheuristic search and evolutionary algorithms to generate covering arrays for combinatorial testing. They include, among others, genetic algorithms, simulated annealing, tabu search, and particle swarm optimization. 1 Methods for Solving Optimization Problems As we mentioned earlier, it is a difficult problem to find small covering arrays.

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Automatic Generation of Combinatorial Test Data by Jian Zhang


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