Big O and Performance

We are very interested in performance ( efficiency, complexity) of algorithms and how the cost of an algorithm increases as the size of the problem increases. Cost can include:

• Time required
• Space (memory) required
• Network bandwidth

Understanding Big O is important to us:

• In many cases, Big O is the deciding factor in choosing a data structure or algorithm.

• We need to be cognizant of Big O when writing code: even a single line of code can raise the Big O of an application, making it unusable.