Optimization Pain

algorithm Big o interview Time-complexity Optimization data structures Technical interview Coding interview

Algorithms Programming

1 hour ago 25,483 views 0 shares

Optimization Pain

algorithm-memes, big-o-memes, interview-memes, time-complexity-memes, optimization-memes | ProgrammerHumor.io

You've already achieved logarithmic time complexity—literally one of the best performance tiers you can get for most algorithms. You're sitting pretty with your binary search or balanced tree traversal. And then the interviewer, with the audacity of someone who's never shipped production code, asks if you can "optimize it further."

Brother, what do you want? O(1)? Do I look like I can predict the future? Should I just hardcode the answer? The only thing left to optimize is my patience and your expectations.

Fun fact: O(log n) is already considered optimal for many search and divide-and-conquer problems. Going from O(log n) to O(1) usually requires either massive space trade-offs or a complete rethinking of the problem. But sure, let me just casually break the laws of computational complexity real quick.

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