Patent ID: 8621305

Claim:
A method for determining whether a built-in-test fault code (BITFC) data sequence generated by a built-in-test (BIT) of a particular module of a complex system is indicative of an actual fault condition, the method comprising: generating a regression function for the particular module based on stored built-in-test fault code (BITFC) data sequences generated by the BIT for the particular module and stored repair data for the particular module, wherein the regression function correlates some particular BITFC data sequences with a finding of an actual fault condition found (FF) result at the particular module, and correlates other particular BITFC data sequences with a finding of no fault condition found (NFF) result at the particular module; executing the BIT at the particular module during operation of the particular module to generate a new BITFC data sequence; and applying, at a processor, the regression function to the new BITFC data sequence to determine whether the new BITFC data sequence is indicative of an actual fault condition at the particular module or is indicative of a false fault condition at the particular module, wherein the step of generating a regression function, comprises: loading, from a fault history database, the stored BIT fault code data sequences generated by the BIT for the particular module and the stored repair data, wherein the stored repair data comprises actual fault condition found (FF) result data and no fault condition found (NFF) result data corresponding to the stored BIT fault code data sequences for the particular module, wherein the actual fault condition found (FF) result data indicates that a particular BIT fault code data sequence generated by the BIT corresponded to an actual fault condition found (FF) result, and wherein the no fault condition found (NFF) result data indicates that the particular BIT fault code data sequence generated by the BIT corresponded to a false alarm (NFF) result; processing the stored BIT fault code data sequences and the stored repair data to generate sorted words that are sorted by length and frequency, wherein each word corresponds to a plurality of symbols that are part of a symbol sequence, wherein each symbol is an identifier that corresponds to a particular BIT fault code, and wherein each word ranges between two and n symbols in length, where n is an integer; using the sorted words to generate feature vectors comprising a first feature vector for a first data class that corresponds to the no fault condition found (NFF) result data, and a second feature vector for a second data class that corresponds to actual fault condition found (FF) result data; and generating, based on the first and second feature vectors, the regression function.