Common Complexity Scenarios
This lesson summarizes our discussion of complexity measures and includes some commonly used examples and handy formulae to help you with your interview.
List of important complexities
The following list shows some common loop statements and how much time they take to execute.
Simple for loop  with an increment of size 1
for (int x = 0; x < n; x++) {
    //statement(s) that take constant time
}
Running time complexity = T(n) = . Dropping the leading constants . Dropping lower order terms .
Explanation: Java for loop increments the value x by 1 in every iteration from 0 until n-1 ([0, 1, 2, …, n-1]). So, n is first 0, then 1, then 2, …, then n-1. This means the loop increment statement x++ runs a total of  times. The comparison statement x < n ; runs  times. The initialization x = 0; runs once. Summing them up, we get a running time complexity of the for loop of . Now, the constant time statements in the loop itself each run  times. Supposing the statements inside the loop account for a constant running time of  in each iteration, they account for a total running time of  throughout the loop’s lifetime. Hence, the running time complexity is .
for loop with increments of size k
for (int x = 0; x < n; x+=k) {
    //statement(s) that take constant time
}
Running time complexity = =
Explanation: The initialization x = 0; runs once. Then, x gets incremented by k until it reaches n. In other words, x is incremented to []. Hence, the incrementation part x+=k of the for loop takes  time.  The comparison part of the for loop takes the same amount of time and one more iteration for the last comparison. So this loop takes  time. The statements in the loop itself take  ...