Algorithms Analysis 2025 – 400 Free Practice Questions to Pass the Exam

The correct response to the question reflects a fundamental aspect of computational complexity theory. NP, which stands for "nondeterministic polynomial time," is defined as the class of decision problems for which a given solution can be verified in polynomial time by a deterministic Turing machine. This means that if you have a proposed solution to a problem in NP, you can check whether this solution is correct quite efficiently.

Contrarily, the set of decision problems that can be solved in polynomial time is referred to as P. So, while all problems in P are also in NP (since any solution that can be computed in polynomial time can certainly be verified in polynomial time), not all problems in NP are known to be solvable in polynomial time. The relationship between P and NP is one of the central questions of computer science – specifically, whether P equals NP or not remains an open question.

By recognizing that NP encompasses problems where solutions can be verified quickly rather than necessarily solved quickly, it clarifies why the assertion about NP being the set of problems that can be solved in polynomial time is false.