Module 1 ยท Complexity and how to think out loud Lesson 4 of 15
Numbers you should know cold
Base cases exist for a reason: for n up to 10, a nested loop is fine; for n up to 100,000 it is not. The n bound in the question tells you which solution is acceptable.
The concept
A few facts save time and make you look prepared. An array index is O(1); searching a sorted array with binary search is O(log n) โ about 20 steps for a million items. A hash map lookup is O(1) on average. Sorting is O(n log n). Counting from 1 to 10โท in a loop is about a second in Python.
Also worth knowing: 10โถ operations is comfortable, 10โธ is not, and that is why an O(nยฒ) solution over 100,000 items cannot pass a time limit no matter how clean it is. When you propose an approach, mention the size of the input it must handle โ the constraints are printed in the question and interviewers expect you to read them.
arr[i] O(1)
binary search O(log n) ~20 steps for 1,000,000 items
hash map lookup O(1) average
sort O(n log n)
loop to 10^7 in Python ~1 second
10^6 ops = comfortable. 10^8 ops = too slow. Read the constraints FIRST.Common mistakes
The mistake is proposing a solution the constraints cannot support and discovering it at the end. Read the limits first, sanity-check the complexity against them, then choose the approach. Three seconds of arithmetic saves the round.
Worked example
A question with n up to 10โต rules out anything O(nยฒ) before you write it โ knowing that saves the interview.
Your practice task
For each of your ten problems, write the largest n that could be accepted with your solution.
Do this before moving on. Reading a solution teaches the shape of it; typing it teaches you.
Key takeaway
A few facts save time and make you look prepared.
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