NP-completeness
NP-completeness is a fundamental concept in Computational complexity theory, which studies the resources required to solve computational problems. A problem is considered NP-complete if it is at least as hard as the hardest problems in NP. NP-complete problems are characterized by their ability to be verified in Polynomial time, but not necessarily solved in polynomial time. The concept of NP-completeness was introduced by Stephen Cook and has since been extensively studied in the field of Computer science. NP-complete problems are often solved using Approximation algorithms or Heuristics, as exact solutions are not feasible for large instances. The study of NP-completeness has led to important advances in Cryptography and Optimization techniques.