Pashchenko Dmitriy Vladimirovich, Doctor of engineering sciences, professor, head of sub-department of computer engineering, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Trokoz Dmitriy Anatol'evich, Candidate of engineering sciences, associate professor, sub-department of computer engineering, Penza State University (40 Krasnaya street, Penza, Russia), firstname.lastname@example.org
Martyashin Georgiy Viktorovich, Master’s degree student, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Maksimova Kristina Stanislavovna, Master’s degree student, Penza State University (40 Krasnaya street, Penza, Russia), firstname.lastname@example.org
Bal'zannikova Elena Alekseevna, Student, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Background. The research object is the developed functional T language, used for development of distributed control system algorithms. The research subject is a way of representing the functional language in the form of a network model based on coloured safe recursive hierarchical Petri nets. The purpose of the work is to formally describe the T language in the form of a network model for its further use in design and presentation of parallel computing systems.
Materials and methods. The T language was formally described using a model of safe recursive hierarchical coloured Petri nets.
Results. The authors defined and described limitations of the T language. The article shows the features of introduction of the language in the form of a network model based on Petri nets.
Conclusions. The authors propose a special kind of functional languages - the T language, intended to describe distributed automated control system algorithms. The proposed method of presentation of the language will make it possible to design a scheme, described in the T language, using the mathematical apparatus of Petri nets. Besides the presented method, the scheme can be described by methods of tensor calculus, as well as translation methods of obtained network models transformation.
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