Evaluating time complexity
Some problems can be solved in many ways with different complexity.
For example, an array of n numbers can be sorted in O(n²) steps - (in a naive way) or in O(n*logn) steps (in an optimal way).
For 1000 numbers, naive sorting will require about 1000000 steps, whereas optimal sorting will need only 10000 - that's 100 times less.
For sufficiently big sets of input data our system can help to determine the complexity of the algorithm, based on execution time.