Archivio Istituzionale della RicercaThis paper presents an approach for performing functional diagnosis of complex systems by means of data mining. The technique allows to derive a set of rules from a functional model of the system for efficiently driving the diagnosis procedure towards the identification of the most promising faulty candidate. The approach is adopted within an incremental method, to limit the number of tests to be performed, thus reducing costs and effort.
Board-level functional fault diagnosis using data mining / Bolchini, C.; Quintarelli, E.; Garza, Paolo. - (2013). (Intervento presentato al convegno Second Workshop on Manufacturable and Dependable Multicore Architectures at Nanoscale (MEDIAN'13)).
Board-level functional fault diagnosis using data mining
GARZA, PAOLO
2013
Abstract
This paper presents an approach for performing functional diagnosis of complex systems by means of data mining. The technique allows to derive a set of rules from a functional model of the system for efficiently driving the diagnosis procedure towards the identification of the most promising faulty candidate. The approach is adopted within an incremental method, to limit the number of tests to be performed, thus reducing costs and effort.
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https://hdl.handle.net/11583/2514491
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