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Step 1: Understanding the term "NP"
In the field of computer science, particularly in the study of computational complexity theory, "NP" stands for "Nondeterministic Polynomial time." This is a classification of decision problems (problems with a "yes" or "no" answer) that can be solved quickly by a nondeterministic Turing machine. In simpler terms, NP problems are those where an efficient algorithm exists to verify a given solution, even if finding that solution might take a long time.
Step 2: NP problems and their solutions
NP problems are characterized by their solutions being efficiently verifiable. This means that, given a potential solution, it can be checked quickly whether it is indeed a valid solution. A classic example of an NP problem is the Boolean satisfiability problem (SAT). In this problem, we are given a Boolean expression consisting of various clauses, and the goal is to find an assignment of truth values to the variables that makes the entire expression true. While finding such an assignment can be challenging, checking whether a given assignment satisfies the expression is straightforward.
Final Answer
"NP" is a classification in computational complexity theory that refers to Nondeterministic Polynomial time. It represents decision problems with efficiently verifiable solutions. NP-completeness is a crucial concept, as it helps assess the difficulty of solving a problem and the potential for finding an efficient algorithm.
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