Complexity of time and space

Complexity of Time

The simple understanding of time complexity is the number of lines that execute the statement. If there are loops and recursion, the simple statement is ignored, and the number of statements executed by the loop and recursion is calculated directly.

Like what:

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1. int x = 1; Time Complexity of O (1)
2. for (int i=0; i<n; i++) {
3. System.out.println (i);
4. }//Time complexity of O (n)

Specific examples:

1, O (1)

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1. int x = 1;

2, O (n)

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1. for (int i=0; i<n; i++) {
2. System.out.println (i);
3. }

3. O ()

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1. int n = 8, count = 0;;
2. for (int i=1; I<=n; i *= 2) {
3. count++;
4. }

4.

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1. int n = 8, count = 0;;
2. for (int i=1; I<=n; i++) {
3. for (int j=1; J<=n; J + +) {
4. count++;
5. }
6. }

5.

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1. int n = 8, count = 0;;
2. for (int i=1; i<=n; i *= 2) {
3. For (int j=1; j<=n; J + +) {
4. count++;
5. }
6. }

The examples are relatively simple.

Complexity of space

Spatial complexity is also a simple understanding of the storage space occupied by temporary variables. A simple example:

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1. Swap two variables x and y
2. int x=1, y=2;
3. int temp = x;
4. x = y;
5. y = temp;

A temporary variable temp, so the spatial complexity is O (1).

Transferred from: http://blog.csdn.net/qiantujava/article/details/12898461

Time complexity and spatial complexity (RPM)