Theoretical Computer Science and Computational Systems 

Theoretical Computer Science at MetodX is focused on the study of the fundamental limits of computation, algorithmic complexity, and the development of new architectures for information processing. The primary objective of this research direction is to analyze the structure of computational problems and to develop methods that enable efficient work with challenges where traditional algorithmic approaches are insufficient.

Modern complexity theory classifies problems according to their computational difficulty. The key classes — P, NP, PSPACE, EXPTIME, and EXPSPACE — define the fundamental boundaries of what can be solved efficiently and what requires exponential computational resources.

Within the MetodX research framework, a systematic analysis is conducted of computational complexity problems across the principal classes of algorithmic theory.

These studies are aimed at identifying the structural properties of these classes, exploring the relationships between them, and developing methods for analyzing problems of extremely high computational complexity.

In addition to fundamental research in complexity theory, this direction also includes the development of practical information processing systems, including new network protocols and intelligent analytical platforms.