The term NP-Complete refers to a complexity class of decision problems. A "complexity class" is simply a collection of computational problems that all have the same bounds on time and space, and a "decision problem" is a problem for which the answer is "yes" or "no." This is equivalent to a computational function that has a range comprising just two discrete values, such as 0 and 1.

NP-Complete is a subset of NP or "Non-deterministic Polynomial time," which is a set of problems for which answers can be checked by an algorithm whose run time is polynomial in the size of the input. The complexity of algorithms is generally measured using "Big-O" notation, which is a theoretical measure of how quickly an algorithm will run in terms of the time or computer memory required given the size of the problem itself. The number of items in the problem typically defines...