  In this paper, we study decision trees for diagnosis of constant faults in
switching networks. Each constant fault consists in assigning Boolean constants
to some edges of the network instead of literals. The problem of diagnosis is
to recognize the function implemented by the switching network with a constant
fault from a given set of faults. For this problem solving, we use decision
trees. Each query (attribute) of a decision tree consists of observing the
value of function implemented by the faulty switching network on a given tuple
of variable values. We study the depth of decision trees for diagnosis of
arbitrary and specially constructed switching networks and the complexity of
diagnostic decision tree construction.
