Maximization of power dissipation under random excitation for burn-in testing

This work proposes an approach to generate weighted random patterns which can maximally excite a circuit during its burn-in testing. The approach is based on a probability model and a maximization procedure to obtain signal transition probability distribution for primary inputs and to generate weighted random patterns according to the obtained probability distribution. It can especially generate weighted random patterns to excite particularly selected `weak nodes' of the circuit in order to expose the early failure of these nodes. Experimental results show that this approach can increase the power dissipation of the total circuit nodes up to 26.68% and the switching activity of particularly selected nodes up to 41.51% respectively.