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Grouped Genetic Algorithm Based Optimal Tests Selection for System with Multiple Operation Modes

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Abstract

To insure various operation modes operated properly, important modules or potential fault sources must be monitored. Due to the hardware resource limit, only part of modules and potential faults can be covered by online test. The percentage of modules or fault sources been covered is termed as fault detection rate (FDR). Lower mode FDR constraints must be satisfied to insure the whole mission executed successfully. It’s a typical multi-constraint optimization problem. In this paper, a grouped genetic algorithm (GGA) is proposed to minimize the test cost and satisfy the FDR constraints. Each GA is used to optimize the test set for one mode. The final chromosome of each GA represents the selected tests in one mode. The union set of the chromosomes of all GAs gives the final solution. Each GA is subjected to one FDR constraint, therefore, the optimal solution is more likely be found. The group of GAs are executed in parallel, hence, the proposed method is efficient. The effectiveness and efficiency of the proposed method are verified by statistical experiments.

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Acknowledgements

This work was supported in part by the Fundamental Research Funds for the Central Universities of China (Grant No. ZYGX2015J074).

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Authors and Affiliations

  1. University of Electronic Science and Technology of China (UESTC), Chengdu, China

    ChengLin Yang & Shulin Tian

  2. Chengdu College, UESTC, Chengdu, China

    Fang Chen

Authors
  1. ChengLin Yang
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  2. Fang Chen
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  3. Shulin Tian
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Correspondence to ChengLin Yang.

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Responsible Editor: A. Ivanov

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Yang, C., Chen, F. & Tian, S. Grouped Genetic Algorithm Based Optimal Tests Selection for System with Multiple Operation Modes. J Electron Test 33, 415–429 (2017). https://doi.org/10.1007/s10836-017-5672-y

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  • DOI: https://doi.org/10.1007/s10836-017-5672-y

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