Algorithmic Time Complexity
Time complexity is a measure of how efficiently an algorithm runs, or how much computational power it requires to execute. Time complexity is usually expressed as a function of the size of the input data, and is used to compare the efficiency of different algorithms that solve the same problem. It helps in determining which algorithm is more suitable for large datasets or real-time applications.
Areas of application
- Search Engines
- Predictive Analytics
- Network Security
- Operating Systems
- Data Mining
- Software Development
- Cloud Computing
- Database Systems
Example
For example, an algorithm with a time complexity of O(n^2) will take longer to run as the size of the input data increases, compared to an algorithm with a time complexity of O(n), which will run faster as the size of the input data increases.