Abstract
This paper describes an approach to testing artificial neural networks that is implemented in a C++ program as a set of data structures and algorithms for their processing. C++ classes are used as data structures that implement the processing of the following objects: vertex, edge, directed and undirected graphs, spanning tree, and circuit. Interfaces for the most important overloaded operations on these objects are described. The implementation of a testing procedure that uses overloaded operations on graph model objects is illustrated.
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ACKNOWLEDGMENTS
We are grateful to Viktor Vasilyevich Malyshko, Associate Professor at the System Programming Department of the Faculty of Computational Mathematics and Cybernetics (CMC), Moscow State University, who assisted in verifying and refining the class diagram of the graph model.
Funding
This work was supported by the Russian Foundation for Basic Research, project nos. 18-07-0697-a, 18-07-01211-a, 19-07-00321-a, and 19-07-00493-a.
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Not long before this publication, one of the co-authors of our work, Yurii Gennad’evich Smetanin, untimely passed away.
We shall always remember him as our friend, a true scientist, and a very good person.
Translated by Yu. Kornienko
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Karpov, Y.L., Volkova, I.A., Vylitok, A.A. et al. Designing Interfaces for Classes of a Neural Network Graph Model. Program Comput Soft 46, 463–472 (2020). https://doi.org/10.1134/S036176882007004X
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DOI: https://doi.org/10.1134/S036176882007004X