Data Structures - Asymptotic Analysis

exponential

2^O(n)

Average Case

Average time required for program execution

Theta Notation

Formal way to express both the lower bound and the upper bound of an algorithms's running time.

Omega Notation

Formal way to express the lower bound of an algorithm's running time. It measures the best case complexity of the best amount of time an algorithm can possibly take to complete.

Worst Case

Maximum time required for program execution

Best Case

Minimum time required for program execution

constant

O(1)

logarithmic

O(log n)

n log n

O(n log n)

linear

O(n)

quadratic

O(n^2)

cubic

O(n^3)

Big o Notation

formal way to express the upper bound of an algorithm's running time. It measures the worst case time complexity or the longest amount of time an algorithm can possibly take to complete

polynomial

n^O(n)