We can create a table with some values to exemplify the cost of the algorithm given its input size as follows:
| Input Size (n) | O(1) | O(log (n)) | O(n) | O(n log(n)) | O(n2) | O(2n) |
| 10 | 1 | 1 | 10 | 10 | 100 | 1,024 |
| 20 | 1 | 1.30 | 20 | 26.02 | 400 | 1,048,576 |
| 50 | 1 | 1.69 | 50 | 84.94 | 2,500 | Very big number |
| 100 | 1 | 2 | 100 | 200 | 10,000 | Very big number |
| 500 | 1 | 2.69 | 500 | 1,349.48 | 250,000 | Very big number |
| 1,000 | 1 | 3 | 1,000 | 3,000 | 1,000000 | Very big number |
| 10,000 | 1 | 4 | 10,000 | 40,000 | 10,000,0000 | Very big number |
We can draw a chart based on the information presented in the preceding table to display the cost of different big O notation complexities as follows:
The preceding chart was also plotted using JavaScript. You can find its source code in the examples/chapter15 ...
