Planning, tracking and projecting method for testability growth based on in time correction

Abstract

A practical mathematic model for in time correction–based testability growth test is proposed in this article. This model can make up the gap between the testability growth test practice and theory. The process of testability design defects identification and correction is formulated, based on which the testability growth test plan optimization method is given with the minimum test cost criterion. A Bayes approach is studied to track the testability growth from the test data. Then the tracked results are used to learn the system correction skill and to project the subsequent testability growth test. Simulation results show that the models and methods presented in this paper are reasonable and can efficiently manage the in time correction–based testability growth test planning, tracking, and projecting problem.