8 added 177 characters in body
source | link

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

7 replaced http://stackoverflow.com/ with https://stackoverflow.com/
source | link

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

6 replaced http://cs.stackexchange.com/ with https://cs.stackexchange.com/
source | link

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.

In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.

For a list of the names and classic examples on Wikipedia: Orders of common functions

Related material:

    Post Made Community Wiki by Thomas Owens
5 Pull in some of the comments. Clean up format.
source | link
4 added 146 characters in body
source | link
3 Clean up link. Reword temporal information.
source | link
2 Added link to Stanford course
source | link
1
source | link