komplexitáselméletben

Komplexitáselméletben is the Hungarian term for "in complexity theory." Complexity theory, within computer science and mathematics, is a field that studies the resources required to solve computational problems. These resources typically include time (how long an algorithm takes to run) and space (how much memory it uses). The primary goal is to classify problems based on their inherent difficulty and to understand the limits of computation.

A central concept in complexity theory is the distinction between problems that can be solved efficiently and those that cannot. Efficiently solvable problems are generally those that can be solved in polynomial time relative to the input size. Problems that are believed to require significantly more time, often exponential time, are considered intractable.

Key areas within complexity theory include the study of complexity classes, such as P (problems solvable in polynomial time) and NP (problems for which a proposed solution can be verified in polynomial time). The famous P versus NP problem, which asks whether P is equal to NP, is one of the most important open questions in computer science. Understanding these classes helps researchers categorize and tackle computational challenges. The theory also investigates the existence and properties of algorithms, the design of efficient data structures, and the fundamental limits on what can be computed.