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

Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning

Neural Network Just a basic Neural Network module Usage Example Importing Module

andreecy 0 Nov 01, 2022
General Assembly Capstone: NBA Game Predictor

Project 6: Predicting NBA Games Problem Statement Can I predict the results of NBA games from the back-half of a season from the opening half of the s

Adam Muhammad Klesc 1 Jan 14, 2022
Official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting

1 SNAS4MTF This repo is the official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting. 1.1 The frame

SZJ 5 Sep 21, 2022
Background Matting: The World is Your Green Screen

Background Matting: The World is Your Green Screen By Soumyadip Sengupta, Vivek Jayaram, Brian Curless, Steve Seitz, and Ira Kemelmacher-Shlizerman Th

Soumyadip Sengupta 4.6k Jan 04, 2023
Pytorch implementation of Decoupled Spatial-Temporal Transformer for Video Inpainting

Decoupled Spatial-Temporal Transformer for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu Sun, Xiaogang Wang, J

51 Dec 13, 2022
Chinese Advertisement Board Identification(Pytorch)

Chinese-Advertisement-Board-Identification. We use YoloV5 to extract the ROI of the location of the chinese word. Next, we sort the bounding box and recognize every chinese words which we extracted.

Li-Wei Hsiao 12 Jul 21, 2022
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images

Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the

163 Sep 21, 2022
Pytorch implementation for the paper: Contrastive Learning for Cold-start Recommendation

Contrastive Learning for Cold-start Recommendation This is our Pytorch implementation for the paper: Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan L

45 Dec 13, 2022
Data augmentation for NLP, accepted at EMNLP 2021 Findings

AEDA: An Easier Data Augmentation Technique for Text Classification This is the code for the EMNLP 2021 paper AEDA: An Easier Data Augmentation Techni

Akbar Karimi 81 Dec 09, 2022
This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.

Lite-HRNet: A Lightweight High-Resolution Network Introduction This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution

HRNet 675 Dec 25, 2022
PyTorch implementation of ENet

PyTorch-ENet PyTorch (v1.1.0) implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation, ported from the lua-torc

David Silva 333 Dec 29, 2022
CVPR2021 Workshop - HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization.

HDRUNet [Paper Link] HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization By Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao an

XyChen 105 Dec 20, 2022
Food recognition model using convolutional neural network & computer vision

Food recognition model using convolutional neural network & computer vision. The goal is to match or beat the DeepFood Research Paper

Hemanth Chandran 1 Jan 13, 2022
A production-ready, scalable Indexer for the Jina neural search framework, based on HNSW and PSQL

🌟 HNSW + PostgreSQL Indexer HNSWPostgreSQLIndexer Jina is a production-ready, scalable Indexer for the Jina neural search framework. It combines the

Jina AI 25 Oct 14, 2022
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models This repository is the official implementation of the fol

DistributedML 41 Dec 06, 2022
An 16kHz implementation of HiFi-GAN for soft-vc.

HiFi-GAN An 16kHz implementation of HiFi-GAN for soft-vc. Relevant links: Official HiFi-GAN repo HiFi-GAN paper Soft-VC repo Soft-VC paper Example Usa

Benjamin van Niekerk 42 Dec 27, 2022
StyleGAN2 with adaptive discriminator augmentation (ADA) - Official TensorFlow implementation

StyleGAN2 with adaptive discriminator augmentation (ADA) — Official TensorFlow implementation Training Generative Adversarial Networks with Limited Da

NVIDIA Research Projects 1.7k Dec 29, 2022
Static-test - A playground to play with ideas related to testing the comparability of the code

Static test playground ⚠️ The code is just an experiment. Compiles and runs on U

Igor Bogoslavskyi 4 Feb 18, 2022
AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation

AtlasNet [Project Page] [Paper] [Talk] AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation Thibault Groueix, Matthew Fisher, Vladimir

577 Dec 17, 2022
Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation

DynaBOA Code repositoty for the paper: Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation Shanyan Guan, Jingwei Xu, Michell

197 Jan 07, 2023