13. Runtime Complexity¶
- More concrete way to decide which solutions is better than the other by looking at the efficiency of algorithms
- Describes the performance of an Algorithms
- How much more processing power/time is required to run your algorithm if we double the inputs?
- Relationship between input and performance e.g. additional processing power required if increase input by 1
- Linear runtime (n) vs. Quadratic runtime (n^2) e.g. reverse string vs. steps
Common Runtime Complexity¶
Big 'O' Notation¶
Another way of referencing runtime complexity, common in academic world
Tips on identifying Runtime Complexity¶
Space Complexity¶
How much more memory is required by doubling the problem set?