Search based software engineering: techniques, taxonomy, tutorial
Empirical Software Engineering and Verification
Optimised realistic test input generation using web services
SSBSE'12 Proceedings of the 4th international conference on Search Based Software Engineering
Controversy Corner: Search Based Software Engineering: Review and analysis of the field in Brazil
Journal of Systems and Software
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Evolutionary testing has successfully applied search based optimization algorithms to the test data generation problem. The existing works use different techniques and fitness functions. However, the used functions consider only one objective, which is, in general, related to the coverage of a testing criterion. But, in practice, there are many factors that can influence the generation of test data, such as memory consumption, execution time, revealed faults, and etc. Considering this fact, this work explores a ultiobjective optimization approach for test data generation. A framework that implements a multi-objective genetic algorithm is described. Two different representations for the population are used, which allows the test of procedural and object-oriented code. Combinations of three objectives are experimentally evaluated: coverage of structural test criteria, ability to reveal faults, and execution time.