Saturation Effects in Testing of Formal Models
ISSRE '02 Proceedings of the 13th International Symposium on Software Reliability Engineering
Reviewing 25 Years of Testing Technique Experiments
Empirical Software Engineering
Evolutionary Multiobjective Optimization: Theoretical Advances and Applications (Advanced Information and Knowledge Processing)
A Characterisation Schema for Software Testing Techniques
Empirical Software Engineering
WoSQ '07 Proceedings of the 5th International Workshop on Software Quality
Model-based testing approaches selection for software projects
Information and Software Technology
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
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The combination of testing techniques is considered an effective strategy to evaluate the quality of a software product. However, the selection of which techniques to combine in a software project has been an interesting challenge in the software engineering field because the high number of techniques available at the technical literature. This paper presents an approach developed to support the combined selection of model-based testing techniques, applying multiobjective combinatorial optimization strategies, by determining the minimum dominating set in a bipartite and bi-weighted graph. Thus, an evolutionary strategy based on a multiobjective genetic algorithm is proposed to generate trade-off techniques subsets between the maximum coverage of software project characteristics and the minimum eventual effort to construct models used for test cases generation. In an empirical evaluation, our evolutionaryalgorithmstrategygavebetterresultsthanthepreviousapproaches.