Fault identification in robust data structures

Abstract

An optimal algorithm is presented for the identification of faulty attributes in a robust data structure. The algorithm does not use any fault syndrome table since the size of such a table could be large, particularly when faults can compensate one another arbitrarily. The data structure is viewed as a collection of data elements related via some attributes. The relationships are specified by a set of axioms in first-order logic. Faults in attributes invalidate some of the axioms. The invalidated axioms are used to identify the faulty attributes. The authors show that the identification is possible in time proportional to the number of axioms even when faults compensate one another arbitrarily. This is optimal since their method of axiom generation does not yield any redundant axioms.<>