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A testability transformation is a source-to-source transformation that aims to improve the ability of a given test generation method to generate test data for the original program. We introduce testability transformation, demonstrating that it differs from traditional transformation, both theoretically and practically, while still allowing many traditional transformation rules to be applied. We illustrate the theory of testability transformation with an example application to evolutionary testing. An algorithm for flag removal is defined and results are presented from an empirical study which show how the algorithm improves both the performance of evolutionary test data generation and the adequacy level of the test data so-generated.