Algorithms Analysis Practice Test 2025 - Free Algorithms Practice Questions and Study Guide

The complexity class of problems that can be verified in polynomial time is known as NP, which stands for "nondeterministic polynomial time." This class includes problems for which, given a candidate solution, there exists a deterministic algorithm that can verify the solution's correctness in polynomial time.

In other words, if you have a proposed solution for an NP problem, you can check whether that solution meets the criteria of the problem efficiently, even if finding that solution in the first place may not be efficient. This characteristic is pivotal in distinguishing NP from other complexity classes, particularly P, which includes problems that can be both solved and verified in polynomial time.

NP is essential in the context of computational complexity theory as it encapsulates many significant and practical problems, including numerous decision problems in computer science. Understanding this helps to frame discussions about algorithms and their efficiency in solving real-world problems.

The other options represent different classes or types of computational problems: P consists of problems that can be solved in polynomial time, NP-hard refers to problems that are at least as hard as the hardest problems in NP but are not necessarily in NP themselves, and Exponential generally refers to problems or algorithms whose time complexity grows exponentially. Each of these classes has its own characteristics and implications in