|
|
|
|
|
by strikelaserclaw
1709 days ago
|
|
some leetcode is good, too much is pretty much useless. There are people who study all solutions to hundreds of leetcode problems to crack the interview, while this hard work is admirable, i feel like they wasted so much time studying that than something that actually makes them a better engineer. For example, i studied Floyd's hare and tortoise algorithm for cycle detection in a linked list a couple months ago, its a beautiful algorithm but i doubt it made me even a little better as a software engineer, that is just one instance of my leetcode adventure, which after a certain point i felt like "man i learned a solution to this random problem which does not extend in a general way to increasing my knowledge and i will most likely forget the solution in a couple months anyway" |
|
1) many Leetcode style solutions are to problems that were at one time practical engineering problems; cycle detection infact is still relevant in cryptography.
2) novel implementations are required all the time in companies that have bandwidth for greenfield projects (ie FAANG). For example, if you search through the source of pytorch (or tensorflow) you will find implementations of the solution to https://leetcode.com/problems/merge-intervals/description/
So everyone always lamenting how useless Leetcode is, is pretty much telling on themselves re the kind of work they do.
Edit: though this isn't what you broach, people that think there's no meaningful difference between eg O(n^2) and O(nlogn) are also broadcasting to the world that they've never run code "at scale". These companies have power bills that are denominated in Bs not Ms and so improving perf by even 1% (on a critical hot path) can be worth millions to the company (and RSU refreshers to you). If you don't believe me then believe Andrei alexandrscu
https://youtu.be/ea5DiCg8HOY?t=175
>So if you shave 1% you've made your salary for 10 years alone