Monograph:

Verification, validation, and testing have become essential in software engineering due to the growing complexity, size of software systems and the pivotal role of software in everyday life. The goal is in revealing high fault, with minimum cost which is targeted by Model Based Testing [MBT]. It is done by automating test case generation in a systematic way from abstract models of the software under test. The total testing cost includes the cost of test execution and evaluation. Automation reduces the test generation cost. Of course, there are some limitations wherein the testing approach in industrial systems cannot be moved scalable. Since all dimensions of the testing cost needs to be addressed. This calls for MBT adjustment in regard to its size of the output test suite. This research proposes different techniques to minimize the test suite size and preserve its fault detection rate which will be higher with more diverse test cases through the techniques called mutual based test case selection and prioritization. Using potential approaches, the research is invited for assigning review on search based techniques for test case generation. The research continues the choice of identifying the effective ways of the best techniques through regions empirical analysis.
To have reliability of the results and the effectiveness of the techniques, influential factors are explained through controlled experiments to analyze the problem. The existing selection techniques and the cost effectiveness of various approaches are also compared in the literature. Complementary study on estimating the best size for a test suite, based on mutation frequency comparisons among the test cases is a significant contribution. The complementary study increases the usability of the techniques proposed where testers are not needed to select an arbitrary test suite size.
To conclude, comparison of mutual based test case selection and prioritization, as the proposed technique proves to be more effective than the existing techniques. MBT is applied to adjust of the output test suite in accordance with the test budget. Hence it shows the significant impact of MBT through this research.

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