These interviews questions are from multiple posts on mitbbs. I find them more interesting than “convert a linked list to a binary tree”-typed interview questions and straight forward questions such as “what is FFT?”, because these questions provide contexts — so they are more like real life problems than merely algorithm exercises.
1. Stock price smoothing, Gaussian smoothing, FFT (Source: Two Sigma?).
2. Influencer, variation of CLRS exerise 22.1-6 “universal sink” (Source: LinkedIn)
3. auto racer, variation of counting inversion (Source: Rocket Fuel)
4. generate random samples from a distribution, Huffman encoding (Source: Google, original article)
5. 2D rainwater trapping, variation of sweep line (Source: Google)
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