Expected Bayesian tracking of testability growth under entropy loss function

Tacking of testability growth test (TGT) is an assurance of the orderly development of TGT. This paper, a testability growth tracking model based on Expected Bayesian method which under entropy loss function is studied in view of the lack of existing testability growth model and the subjective tracking of testability index. Firstly, the multi-layer prior distribution of the fault detection rate (FDR) is obtained by dusing the priori constraint as a priori information. Secondly, under the entropy loss function, the Expected Bayesian method is used as the solution of the multi-layer Bayesian. Finally, the TGT is tracked according to the growth test data of a stable tracking platform. The results show that the method has strong objectivity and the tracking accuracy is in the order of 10
^-2
magnitude.