Every interviewer asks about arrays hashmaps and trees and what is O notation access times to the item in those data structures
And second big interview helper is sorting #algorithms, if you have a photographic memory this would help you
Btw which one is faster O(logn) or O(n) below graphic shows their speed difference
O(logn) is faster than O(n) 🤓
Reference:
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Top comments (3)
This is a great starting point for anyone preparing for coding interviews! I especially appreciate the clear explanation of big O notation and the visual comparison of speeds.
feel free to share if you find a good article on this topic, it is not easy to understand these from one article 🤓
sure