Comparison of the Genetic Algorithms to build a Diagnostic Tree for diagnosing Single Stuck-at Failures
Ekaterina Y. Danilova · 2019
FPGAs are used in various areas of human activity. It is necessary to quickly identify failures for their correct operation. FPGAs are diagnosed to detect failures, finding a place of its occurrence and determining its type. This paper is devoted to algorithms for constructing diagnostic sequences for diagnosing single stuck-at failures. Two genetic algorithms are considered in the paper: GA for constructing a simple diagnostic tree and GA for constructing a diagnostic tree with feedback. The diagnostic feedback tree allows partitioning the set of function classes more efficient. Also, a comparison of the work of two genetic algorithms was made.