Abstract
Mutation testing is a fault-based unit testing in which faults are detected by executing certain test data designed by any white box testing technique. This paper presents a hybridized method for path testing as well as mutation testing by generating the test data automatically using genetic algorithm. In the proposed approach, first path coverage-based test data is generated and further this data is exercised to cover all mutants present in the specific program under test. The proposed method can improve the testing efficiency by deleting the redundant test data obtained from the path testing in terms of better mutation score, and fault detection matrix is used to delete the duplicate data covering same mutants.
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Mishra, D.B., Mishra, R., Acharya, A.A., Das, K.N. (2019). Test Data Generation for Mutation Testing Using Genetic Algorithm. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 817. Springer, Singapore. https://doi.org/10.1007/978-981-13-1595-4_68
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