Potential Interview Questions

Question 1

Event delegation/Event bubbling

Question 2

Big-O Notation

Answer 2

The time complexity (not amount of time for completion) of an algorithm

• 0(1) = constant time (the fastest time possible), the number of operations never grows as the input grows in size
• 0(n) = linear time, each input value is operated on once, example: using a loop to iterate over every element in an array, object, or string
• 0(n^2) = quadratic time, number of operations multiplied by 4 for each doubling of the input size n, example: nested loop
• 0(2^n) = exponential time, extremely slow, the number of operations doubles for each additional input, example: brute-force password search
• 0(n!) = factorial time, slowest time ever

Question 3

AJAX

Question 4

DOM

Question 5

Scope

Question 6

Reference vs Primitive Data Types

Question 7

Closures

Question 8

Callbacks

Question 9

Asynchronous vs Synchronous

Question 10

Event Loop

Question 11

API

Question 12

REPL

Question 13

REST

Question 14

Prototypal Inheritance