Generation of New March Tests with Low Test Power and High Fault Coverage by Test Sequence Reordering Using Genetic Algorithm

March tests have been found to be very effective for fault detection and diagnosis in memories. Effectiveness of a March test is usually decided by the number of faults that can be detected using the test. The more the number of fault models covered, the better the test. March tests with good fault coverage have been developed but the test power also plays an important role in deciding the effectiveness of the test. The test power is directly related to the number of switching activities occurring in the test. The paper deals with the generation of March tests with low test power and good fault coverage by test sequence reordering using a genetic algorithm based approach. A power tool has been developed helps us to calculate the power consumption of a given March test. An algorithm was devised to generate new march tests with optimized test power and fault coverage by reordering the test sequence. The fault coverage and diagnostic capabilities of the novel March test can be verified using the fault simulator tool developed. The use of genetic algorithm helps to generate wide range of test patterns compared to the existing methods.