Computational complexity theory is a branch of computer science that studies the resources required to solve computational problems. It classifies problems based on how difficult they are to solve, often in terms of time and space. This helps in understanding which problems can be solved efficiently and which cannot. One of the key concepts in this field is the distinction between P and NP problems. P problems can be solved quickly by an algorithm, while NP problems can be verified quickly, but finding a solution may take a long time. Understanding these classes helps researchers develop better algorithms and optimize computing processes.