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Software testing is most effort consuming phase in software development. One would like to minimize the efforts and maximize the number of faults detected. Hence test case generation may be treated as an optimization problem. One of the major difficulties in software testing is the automatic generation of test data that satisfy a given adequacy criterion. Generating test cases automatically will reduce cost and efforts significantly. In this paper, test case data is generated automatically using Genetic Algorithms and results are compared with Random Testing. It is observed that Genetic Algorithms outperforms Random Testing.
Automatic test case generation, Equivalence Class Partitioning, Random Testing etc.
Automatic test case generation, Equivalence Class Partitioning, Random Testing etc.
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