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Google Hash Code Challenge Archive

Hash Code is a team programming competition organized by Google for students and industry professionals across Europe, the Middle East and Africa. You pick your team and programming language, we pick a Google engineering problem for you to solve. The competition takes place over two rounds:

🚀 Interactive CLI Tool

This repository now includes a .NET 9.0 CLI application to explore and run Hash Code challenges!

Quick Start

cd src/HashCodeCli
dotnet run

Features

  • Browse all challenges by year
  • View full problem descriptions
  • Read solution explanations
  • Run solutions on challenge input files
  • Beautiful interactive terminal UI

See CLI README for more details.

Online Qualification Round

Your team can participate from one of our competition hubs or from wherever else you’d like.

Final Round

Top scoring teams from the Online Qualification Round will be invited to Google Dublin to compete in the Final Round of the competition.

Editions

2018

TBD

2017

2016

2015

Final Round

Loon

Project Loon aims to bring universal Internet access using a fleet of high altitude balloons equipped with LTE transmitters. Circulating around the world, Loon balloons deliver Internet access in areas that lack conventional means of Internet connectivity. Given the wind data at different altitudes, plan altitude adjustments for a fleet of balloons to provide Internet coverage to select locations.

Qualification Round

Optimize a data center

For over ten years, Google has been building data centers of its own design, deploying thousands of machines in locations around the globe. In each of these of locations, batteries of servers are at work around the clock, running services we use every day, from Google Search and YouTube to the Judge System of Hash Code. Given a schema of a data center and a list of available servers, your task is to optimize the layout of the data center to maximize its availability.

2014

Street View routing

Hash Code 2014, Final Round

The Street View imagery available in Google Maps is captured using specialized vehicles called Street View cars. These cars carry multiple cameras capturing pictures as the car moves around a city. Capturing the imagery of a city poses an optimization problem: the fleet of cars is available for a limited amount of time and we want to cover as much of the city streets as possible.

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