Big - O

Question 1

What is Big-O?

Answer 1

Big-O notation is an assessment of an algorithm’s efficiency. Big-O notation helps gauge the amount of work that is taking place.

Question 2

What does the Big-O notation look like for:

1) constant
2) logarithmic
3) linear

Answer 2

1) O(1)
2) O(log2 N)
3) O(N)

Question 3

What does the Big-O notation look like for:

1) linearithmic
2) quadratic
3) exponential

Answer 3

1) O(N log2 N)
2) O(N2)
3) O(Nn)

Question 4

Why do we need to know the Big-O Notation?

Answer 4

One of the main reasons for consulting Big-O is to make decisions about which algorithm to use for a particular job.

Question 5

How do you apply a Big-O notation?

Answer 5

In order to properly apply a BigO notation, it is important to analyze a piece of code to see what the code is doing and how many times it is doing it.

Question 6

What’s the formal defintion for Big-O?

Answer 6

BigO is bound(N) if runTime(N) <= c * bound(N)

Question 7

What are some things to consider then determining the Big-O?

Answer 7

It’s determined by the most restrictive Big-O possible so that the Big-O grows at a faster rate than the actual runtime of the code.