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Research on Analog Integrated Circuit Test Parameter Set Reduction Based on XGBoost

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Abstract

As the scale of integrated circuits continues to increase and their test cost increases with test time, how to optimize the test parameters is an important topic. In analog integrated circuits, the implicit dependency among test parameters makes it possible to apply the XGBoost technique based on decision trees in machine learning to optimize the test parameters. In this paper, an optimization algorithm is proposed based on the XGBoost decision tree model. By modeling the representational relationships of each test parameter in the historical test data set, the list of those to be optimized is obtained according to the descending order of the escape rate in the prediction results. According to this list, the test parameters to be deleted are selected in turn, the prediction results of the remaining test parameters on those test parameters are obtained, and the escape rate after screening out the target parameters is evaluated, and the test parameters are optimized based on this list to reduce the test time and test cost.

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Data Availability

The data that support the findings of this study are available from [Xi’an Microelectronic Technology Institute] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [Xi’an Microelectronic Technology Institute].

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant 61871089 and Key Laboratory of Automatic Testing Technology and Instruments under Grant YQ201202.

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Authors and Affiliations

  1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Yindong Xiao, Yutong Zeng, Qiong Wu, Ke Liu & Yanjun Li

  2. Guangxi Key Laboratory of Automatic Testing Technology and Instruments, Guilin University of Electronic Technology, Guilin, China

    Chong Hu

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  1. Yindong Xiao
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  2. Yutong Zeng
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  4. Ke Liu
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  5. Yanjun Li
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Correspondence to Yanjun Li.

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Xiao, Y., Zeng, Y., Wu, Q. et al. Research on Analog Integrated Circuit Test Parameter Set Reduction Based on XGBoost. J Electron Test 38, 279–288 (2022). https://doi.org/10.1007/s10836-022-06009-8

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