Abstract
An algorithm is presented for designing minimum-expected-cost test trees for detecting and isolating single faults in a system. A test is specified by the subset of components that must be good for the test to pass, and with each test is associated a fixed cost. Each component is assumed to have an a priori probability of failure. The test tree specifies an adaptive testing procedure that detects a failure and isolates the faulty component while minimizing the expected cost of testing.
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