Efficient Algorithm Selection for Detecting Suitable Test Case Prioritization

Genetic algorithms have been successfully applied in the area of software testing. The demand for automation of test case generation in object oriented software testing is increasing. Genetic algorithms are well applied in procedural software testing but a little has been done in testing of object oriented software. This paper discusses genetic algorithms that can automatically select an efficient algorithm which is suitable for test cases selection. This algorithm takes a selected path as a target and executes sequences of operators iteratively for efficient algorithm selection to evolve. The evolved efficient algorithm selection can lead the program execution to achieve the target path. An automatic path-oriented test data generation is not only a crucial problem but also a hot issue in the research area of software testing today. We also propose genetic algorithm for the selection of the suitable algorithm, which perform much better than the existing methods and can provide very good solutions.

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