ps aux | grep ssh | awk '{print $2}' | xargs kill -9

### How to deal with time complexity?

- Use data structures with good time complexity for basic operations.
- Use libraries with good time complexity for basic operations.
- Measure time complexity of the code.
- Look for bottlenecks.
- Think about time complexity before writing the code.

### Space Complexity

- Space complexity of an algorithm quantifies the amount of space or memory taken by an algorithm to run as a function of the length of the input.

- Space complexity needs to be taken seriously for multi-user systems, embedded systems, and systems where memory is at a premium.

- Space complexity includes both Auxiliary space and space used by input.

- Auxiliary space is the extra space or temporary space used by an algorithm.

- Space complexity of an algorithm is mostly the function of input size.

- Example: If the input size is n, then space complexity can be O(1), O(n), O(n2), O(log n), O(n log n), etc.

- Space complexity can be defined as a function relating the input length to the space required by the algorithm.