Genetic algorithm for test pattern generator design
作者:Tomasz Garbolino, Gregor Papa
摘要
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.
论文关键词:Optimization, Genetic algorithm, Design, Test pattern generator
论文评审过程:
论文官网地址:https://doi.org/10.1007/s10489-010-0214-7