Test data regeneration: generating new test data from existing test data

Existing automated test data generation techniques tend to start from scratch, implicitly assuming no pre-existing test data are available. However, this assumption may not always hold, and where it does not, there may be a missed opportunity; perhaps the pre-existing test cases could be used to assist the automated generation of additional test cases. This paper introduces search-based test data regeneration, a technique that can generate additional test data from existing test data using a metaheuristic search algorithm. The proposed technique is compared to a widely studied test data generation approach in terms of both efficiency and effectiveness. The empirical evaluation shows that test data regeneration can be up to two orders of magnitude more efficient than existing test data generation techniques, while achieving comparable effectiveness in terms of structural coverage and mutation score.