An Efficient Dictionary Organization for Maximum Diagnosis

The major problem of fault diagnosis with a fault dictionary is the enormous amount of data. The technique used to manage this data can have a significant effect on the outcome of the fault diagnosis procedure. If information is removed from a fault dictionary in order to reduce the size of the dictionary, its ability to diagnose stuck-at faults and unmodeled faults may be severely debased. Therefore, we focus on methods for producing a dictionary that is both small and lossless-compacted. We propose an efficient dictionary for maximum diagnosis, which is called SD-Dictionary. This dictionary consists of a static sub-dictionary and a dynamic sub-dictionary in order to make a smaller dictionary while maintaining the critical information needed for the diagnostic ability. Experimental results on ISCAS’ 85, ISCAS’ 89 and ITC’ 99 benchmark circuits show that the size of the proposed dictionary is substantially reduced, while the dictionary retains most or all of the diagnostic capability of the full dictionary.