Computational complexity theory (nonfiction)

Computational complexity theory is a branch of the theory of computation in theoretical computer science and mathematics (nonfiction) that focuses on classifying computational problems according to their inherent difficulty, and relating those complexity classes to each other.

A computational problem is understood to be a task that is in principle amenable to being solved by a computer, which is equivalent to stating that the problem may be solved by mechanical application of mathematical steps, such as an algorithm (nonfiction).

A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used.

The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying the amount of resources needed to solve them, such as time and storage.

One of the roles of computational complexity theory is to determine the practical limits on what computers can and cannot do.

Fiction cross-reference

• Gnomon algorithm

Nonfiction cross-reference

• Algorithm (nonfiction)
• Computation (nonfiction)
• Computer science (nonfiction)
• Evil bit (nonfiction)
• Gnomon (nonfiction)
• Gnomon Algorithm (nonfiction)
• Mathematical function (nonfiction)
• Mathematics (nonfiction)
• Measurement (nonfiction)
• Theory of computation (nonfiction)

External links:

• Computational complexity theory @ Wikipedia