The growing complexity and dependability requirements of hardware, software, and networks demand efficient techniques for discovering disruptive behavior in those systems. Comparison-based diagnosis is a realistic approach to detect faulty units based on the outputs of tasks executed by system units. This survey integrates the vast amount of research efforts that have been produced in this field, from the earliest theoretical models to new promising applications. Key results also include the quantitative evaluation of a relevant reliability metric—the diagnosability—of several popular interconnection network topologies. Relevant diagnosis algorithms are also described. The survey aims at clarifying and uncovering the potential of this technology, which can be applied to improve the dependability of diverse complex computer systems.
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Duarte et al. (2011) studied this question.
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