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PAPER 1 - ⇑ Theory of computation ⇑
← Maths for big-O notation	Order of complexity	Limits of computation →

Order of Complexity

Notation	Name	Example
$O(1)\,$	constant	Determining if a number is even or odd; using a constant-size lookup table
$O(\log n)\,$	logarithmic	Finding an item in a sorted array with a binary search or a balanced search tree as well as all operations in a Binomial heap.
$O(n)\,$	linear	Finding an item in an unsorted list or a malformed tree (worst case) or in an unsorted array; Adding two n-bit integers by ripple carry.
$O(n\log n)=O(\log n!)\,$	linearithmic, loglinear, or quasilinear	Performing a Fast Fourier transform; heapsort, quicksort (best and average case), or merge sort
$O(n^{2})\,$	quadratic	Multiplying two n-digit numbers by a simple algorithm; bubble sort (worst case or naive implementation), Shell sort, quicksort (worst case), selection sort or insertion sort
$O(n^{c}),\;c>1$	polynomial or algebraic	Tree-adjoining grammar parsing; maximum matching for bipartite graphs
$O(c^{n}),\;c>1$	exponential	Finding the (exact) solution to the travelling salesman problem using dynamic programming; determining if two logical statements are equivalent using brute-force search
$O(n!)\,$	factorial	Solving the travelling salesman problem via brute-force search; generating all unrestricted permutations of a poset; finding the determinant with expansion by minors.