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Genetic algorithm for test pattern generator design
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DOI：10.1007/s10489-010-0214-7.png)
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The paper describes an approach for the generation of a deterministic test pattern generator logic, which is composed of D-type and T-type flip-flops. This approach employs a genetic algorithm that searches for an acceptable practical solution in a large space of possible implementations. In contrast to conventional approaches the proposed one reduces the gate count of a built-in self-test structure by concurrent optimization of multiple parameters that influence the final solution. The optimization includes the search for: the optimal combination of register cells type; the presence of inverters at inputs and outputs; the test patterns order in the generated test sequence; and the bit order of test patterns. Results of benchmark experiments and comparison with similar studies demonstrate the efficiency of the proposed evolutionary approach.
Keyword:
Optimization
Genetic algorithm
Design
Test pattern generator
期刊
IF:
3.5
论文数:
7.6K
被引数:
1.7W
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APPLIED INTELLIGENCE
APPLIED INTELLIGENCEIF3.5
PREAI
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