Preparation material for Dropbox interviews

Overview

Dropbox-Onsite-Interviews

A guide for the Dropbox onsite interview!

The Dropbox interview question bank is very small. The bank has been in a Chinese forum for many years now, and we would like to make it accessible to everyone so that everyone will have an equal opportunity to prepare for the Dropbox onsite interview!

https://1o24bbs.com/t/topic/1381

Backup link: https://web.archive.org/web/20210224003004/https://1o24bbs.com/t/topic/1381


Behavioral Questions:

Talk about an impactful project that you led.

  • Teams that you collaborated with.
  • Convincing others to take action.
  • A tough decision that you had to make during that project.

A critical piece of feedback that you received from someone and what you did after that.

An important piece of feedback that you gave to someone else.

A conflict that you had with someone else.

How do you contribute to diversity and inclusion?


We do not ask for references and we do not check for references.


Coding and System Design Tips

As always, you must talk your way through the problem and explain your reasoning. You should ALWAYS talk about performance (system performance for system design and time/space complexity for the coding problems) and talk about testing, even if the interviewer does not prompt you to.

Coding Question List:

  1. Id Allocator - Create a class that can allocate and release ids. The image in the packet is wrong. Please see this image.

This question is EXTREMELY popular and is asked in most onsite interviews, even if you're not a recent graduate.

Solution

  1. Download File / BitTorrent - Create a class that will receive pieces of a file and tell whether the file can be assembled from the pieces.

This question is mostly for new graduates/phone screens.

  1. Game of Life - Conway's Game of Life - Problem on LeetCode

This question is EXTREMELY popular for phone screens.

Solution

  1. Hit Counter - Design a class to count the hits received by a webpage

This question is mostly on phone screens.

Solution

  1. Web Crawler - Design a web crawler, first single-threaded, then multithreaded.

This question is EXTREMELY popular for onsite interviews.

Solution

  1. Token Bucket

This question is somewhat popular for onsite interviews. It has a multi-threaded component.

Solution

  1. Search the DOM

This question is somewhat popular for roles with a large frontend component.

Question

  1. Space Panorama

Create an API to read and write files and maintain access to the least-recently written file. Then scale it up to a pool of servers.

Solution

  1. Phone Number / Dictionary - Given a phone number, consider all the words that could be made on a T9 keypad. Return all of those words that can be found in a dictionary of specific words.

This question is sometimes asked to college students and sometimes asked in phone screens. It isn't asked a lot in onsites.

Solution

  1. Sharpness Value - This question is usually phrased like "find the minimum value along all maximal paths". It's a dynamic programming question.

Occasionally asked in phone screens. Might be asked in onsites for new hires.

Solution

  1. Find Byte Pattern in a File - Determine whether a pattern of bytes occurs in a file. You need to understand the Rabin-Karp style rolling hash to do well.

Somewhat frequently asked in onsite interviews. Might be asked in phone screens.

Solution

  1. Count and Say - LeetCode. Follow up - what if it's a stream of characters?

Asked to college interns.

Solution

  1. Number of Islands / Number of Connected Components - Find the number of connected components in a grid. Leetcode

Mainly asked to college interns.

Solution

  1. Combination Sum / Bottles of Soda / Coin Change - Find all distinct combinations of soda bottles that add up to a target amount of soda. LeetCode

Mainly asked to IC1 candidates.

Solution

  1. Find Duplicate Files - Given the root of a folder tree, find all the duplicate files and return a list of the collections of duplicate files. LeetCode

Somewhat popular in phone screens. Less common in onsites.

Solution

Satellite labelling tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, rings etc.

Satellite labelling tool About this app A tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, ri

Czech Hydrometeorological Institute - Satellite Department 10 Sep 14, 2022
Data cleaning, missing value handle, EDA use in this project

Lending Club Case Study Project Brief Solving this assignment will give you an idea about how real business problems are solved using EDA. In this cas

Dhruvil Sheth 1 Jan 05, 2022
Posterior temperature optimized Bayesian models for inverse problems in medical imaging

Posterior temperature optimized Bayesian models for inverse problems in medical imaging Max-Heinrich Laves*, Malte Tölle*, Alexander Schlaefer, Sandy

Artificial Intelligence in Cardiovascular Medicine (AICM) 6 Sep 19, 2022
This is the source code for generating the ASL-Skeleton3D and ASL-Phono datasets. Check out the README.md for more details.

ASL-Skeleton3D and ASL-Phono Datasets Generator The ASL-Skeleton3D contains a representation based on mapping into the three-dimensional space the coo

Cleison Amorim 5 Nov 20, 2022
MGFN: Multi-Graph Fusion Networks for Urban Region Embedding was accepted by IJCAI-2022.

Multi-Graph Fusion Networks for Urban Region Embedding (IJCAI-22) This is the implementation of Multi-Graph Fusion Networks for Urban Region Embedding

202 Nov 18, 2022
Video Contrastive Learning with Global Context

Video Contrastive Learning with Global Context (VCLR) This is the official PyTorch implementation of our VCLR paper. Install dependencies environments

143 Dec 26, 2022
VLGrammar: Grounded Grammar Induction of Vision and Language

VLGrammar: Grounded Grammar Induction of Vision and Language

Yining Hong 27 Dec 23, 2022
StellarGraph - Machine Learning on Graphs

StellarGraph Machine Learning Library StellarGraph is a Python library for machine learning on graphs and networks. Table of Contents Introduction Get

S T E L L A R 2.6k Jan 05, 2023
Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

41 Jan 03, 2023
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Hongje Seong 72 Dec 14, 2022
Machine learning for NeuroImaging in Python

nilearn Nilearn enables approachable and versatile analyses of brain volumes. It provides statistical and machine-learning tools, with instructive doc

919 Dec 25, 2022
Deep and online learning with spiking neural networks in Python

Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern

Jason Eshraghian 447 Jan 03, 2023
Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker

Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker This is a full project of image segmentation using the model built with

Htin Aung Lu 1 Jan 04, 2022
Implementation of ResMLP, an all MLP solution to image classification, in Pytorch

ResMLP - Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-py

Phil Wang 178 Dec 02, 2022
This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.

SLATE This is the official source code for SLATE. We provide the code for the model, the training code and a dataset loader for the 3D Shapes dataset.

Gautam Singh 66 Dec 26, 2022
PyTorch implementation of "PatchGame: Learning to Signal Mid-level Patches in Referential Games" to appear in NeurIPS 2021

PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin

Kamal Gupta 22 Mar 16, 2022
Revisiting Self-Training for Few-Shot Learning of Language Model.

SFLM This is the implementation of the paper Revisiting Self-Training for Few-Shot Learning of Language Model. SFLM is short for self-training for few

15 Nov 19, 2022
This repo contains the pytorch implementation for Dynamic Concept Learner (accepted by ICLR 2021).

DCL-PyTorch Pytorch implementation for the Dynamic Concept Learner (DCL). More details can be found at the project page. Framework Grounding Physical

Zhenfang Chen 31 Jan 06, 2023
Video-based open-world segmentation

UVO_Challenge Team Alpes_runner Solutions This is an official repo for our UVO Challenge solutions for Image/Video-based open-world segmentation. Our

Yuming Du 84 Dec 22, 2022
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

Felix Wimbauer 494 Jan 06, 2023