Abstract：To solve the problem of fruit fly optimization algorithm(FOA) effectively,which is easy to trap in local optimal and the low convergence accuracy,an adaptive fruit fly optimization algorithm is proposed based on normal cloud model(CAFOA).Firstly,the conception of sensitive factoris introduced and adjusted adaptively for controlling search step to update location.Then,the randomness and fuzziness of smell concentration parameter is described by normal cloud model and adjusted to finish osphresis search operation automatically,and the detailed steps of CAFOA are given.Finally,this algorithm is used to the automatic test,compared and analyzed with the experiment of other FOA in reference literatures.The results of experiment show that this algorithm has better advantages of test efficiency and accuracy.

Keyword：fruit fly optionization algorithm;normal cloud model;adaption;automatic test;