Abdallah Alhameedyeen, Mohammad Alshraideh, Hazem Hiary



Goal-Oriented Testing for Pointer Data Type

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Software testing is an important phase in software development. Faults can cause serious and costly problems if they are neglected in software development, such as programs used in the fields of medicine, aviation, and military operations. A genetic algorithm (GA) is an evolutionary algorithm that can help to generate test data very quickly and accurately, generating test cases that fit the software under test. in this research, we generate test data for software that contains pointers using GA where these test data are valid for the software regardless of which path to use. The results of the experiments demonstrate that the Genetic Algorithm gives good results once used as test data generators to test pointer data type; such that the test target in all programs under test is reached which means that the percentage of the coverage was (100 %). Also, it shows the effect of using pointers in the source code, where the results were less in terms of execution time and the6 same in terms of the number of generations for a program that does not contain pointers than the same program which contains pointers.


Software testing (SWT), genetic algorithm (GA), pointers, automated software test data generation, metaheuristic search


Cite this paper

Abdallah Alhameedyeen, Mohammad Alshraideh, Hazem Hiary. (2021) Goal-Oriented Testing for Pointer Data Type. International Journal of Computers, 6, 60-67


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