Big O

Question 1

Ways to think

Answer 1

• counting iterations (sum…)
• what it means (pairs, strings, sorts…)
• vizualizing (nxn matrix…)
• average work (average iteration…)
• recursive pattern O(branches^depth)
• rate of increase
  Be careful of n-dependant inside a loop (fib(i)…)

Question 2

2^10/20/30/40

Answer 2

2^10 = 1KB
2^20 = 1MB
2^30 = 1GB
2^40 = 1TB