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Algorithm Complexity Terms
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Recursive Algorithms
Algorithms that solve problems by solving smaller instances of the same problem.
Space Complexity
A measure of the amount of memory an algorithm uses in terms of the size of the input.
Big O Notation
A mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity.
Amortized Analysis
Analyzes the average running time per operation over a sequence of operations to provide a guaranteed average performance.
Master Theorem
Provides a solution to recurrence relations for divide-and-conquer algorithms.
Big Theta Notation
A notation that describes a function's growth in both the upper and lower bounds.
Time Complexity
A measure of the amount of time an algorithm takes to run as a function of the length of the input.
P vs NP Problem
A major unsolved problem in computer science that asks whether every problem whose solution can be quickly verified can also be solved quickly.
Big Omega Notation
A notation used to describe the lower bound of an algorithm's complexity.
NP-Complete
A class of problems that are both NP and as hard as any problem in NP, meaning if one NP-complete problem can be solved quickly, all NP problems can.
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