Improving a GA-based ATPG for Sequential Circuits by Exploiting Dynamically Generated "Essential Sequences"
نویسندگان
چکیده
This paper presents an algorithm that compacts the Test Sequences generated by a GA-based ATPG program for sequential circuits. In this algorithm, from a set of test sequences, a properly selected subset of sequences is reordered and combined without reducing the number of detected faults. By introducing the metric of fault density sequence selection is guided towards sequences that have higher fault density. The identification and exploitation in the GA population of special sequences called essential sequences speeds up the compaction algorithm. Experimental results support the usefulness of the proposed method. Key-Words: Sequential Digital Circuits, Sequence Compaction, Test Generation, Genetic Algorithms.
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