Abstract
This article reviews a class of adaptive group testing procedures that operate under a probabilistic model assumption as follows. Consider a set of items, where item has the probability ( in the generalized group testing) to be defective, and the probability to be non-defective independent from the other items. A group test applied to any subset of size is a binary test with two possible outcomes, positive or negative. The outcome is negative if all items are non-defective, whereas the outcome is positive if at least one item among the items is defective. The goal is complete identification of all items with the minimum expected number of tests.
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