Editing Computational Complexity (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Computational Complexity''' — A branch of the theory of computation that focuses on "Classifying" computational problems according to their "Inherent Difficulty."
* '''Time Complexity''' — How many "Steps" an algorithm takes relative to the size of the input (n).
* '''Space Complexity''' — How much "Memory" an algorithm needs.
* '''Big O Notation''' — The language of complexity (e.g., $O(n)$ is "Linear," $O(n^2)$ is "Quadratic," $O(2^n)$ is "Exponential").
* '''P (Polynomial Time)''' — The class of problems that are "Easy" to solve (e.g., 'Sorting a list').
* '''NP (Nondeterministic Polynomial Time)''' — The class of problems where a solution is "Hard to find" but "Easy to check" (e.g., 'A Sudoku puzzle').
* '''NP-Complete''' — The "Hardest" problems in NP; if you can solve one of these quickly, you can solve **All** NP problems.
* '''The P vs. NP Problem''' — The $1 Million prize question: "Is every problem whose solution can be checked quickly also able to be solved quickly?" (Most believe the answer is 'No').
* '''Exponential Growth''' — The "Killer" of computers; when adding 1 more item to a list "Doubles" the time needed to solve it.
* '''Polynomial Growth''' — The "Friend" of computers; when doubling the input only increases the time by a predictable amount.
</div>

<div style="background-color: #006400; color: #FFFFFF; padding: 20px; border-radius: 8px; margin-bottom: 15px;">