A recognition technology for the output pattern of likely metamorphic relation of neutron diffusion program

Zhaoyu Wen; Xiaohua Yang; Shiyu Yan; Meng Li

doi:10.1117/12.2629106

16 March 2022 A recognition technology for the output pattern of likely metamorphic relation of neutron diffusion program

Zhaoyu Wen, Xiaohua Yang, Shiyu Yan, Meng Li

Author Affiliations +

Proceedings Volume 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021); 121671L (2022) https://doi.org/10.1117/12.2629106
Event: 2021 Third International Conference on Electronics and Communication, Network and Computer Technology, 2021, Harbin, China

Abstract

The metamorphic test is a method to alleviate the unexpected value of the Oracle problem. The key point is the identification of the metamorphic relations. The identification of the metamorphic relations of scientific calculation programs is also a complex problem, and the likely of the metamorphic relation of the program can provide enlightening information for the identification of the metamorphic relations. The likely metamorphic relation can be regarded as the implicit expression of the input pattern and output pattern. This paper proposes an output pattern recognition technology based on the likely metamorphic relations of GEP. The technology is mainly aimed at the core neutron diffusion calculation program. The input pattern of the program, and then generate input data and run the program. Finally, in the corresponding output data results, through GEP data mining technology, the output pattern expressed in a variety of functional forms is obtained, which is further compared with analytical solutions and verified to be reliable likely metamorphic relations.

Citation Download Citation

Zhaoyu Wen, Xiaohua Yang, Shiyu Yan, and Meng Li "A recognition technology for the output pattern of likely metamorphic relation of neutron diffusion program", Proc. SPIE 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021), 121671L (16 March 2022); https://doi.org/10.1117/12.2629106

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