Abstract
A heuristic particle swarm optimization algorithm is proposed to solve the problem of test point selection with unreliable test. Firstly, a heuristic function is established to value the capability of test point detection, coverage and reliance. Then based on the heuristic function and least test cost principle, a fitness function of unreliable test is created. Lastly, the method for test point selection using improved particle swarm optimization algorithm is presented. Comparing with other method of test point selection, the results show that the method is easy to find the global optimal test point in large-scale system. It can also minimize test cost on requirement of testability targets.
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