princeton-algorithms

My solutions to the Princeton Algorithms Courses: Algorithms, Part I and Algorithms, Part II programming assignments on Coursera.

Quick Start

Each project directory comes with the following items:

• Java source code: these are the code submitted to the AutoGrader
• Makefile: which provides 2 routines
  • make submit: which will compress the Java source code into a .zip in out/ for submitting to the AutoGrader
  • make clean: remove directory out/
• logo.png: a nicely looking logo for each project
• .gitignore: which ignores all other files that came with the project boilerplate

Therefore, project-provided resources such as algs4.jar, testing clients, testing data and IDEA workspace settings are not managed by the repo. Please refer to the Project Specifications and Environment Setup for the latest resources of this such.

Projects

Project	Code	Specification	Grade
	Code 💻	Specification 📖	100
	Code 💻	Specification 📖	100
Collinear Points	Code 💻	Specification 📖	100
	Code 💻	Specification 📖	100
	Code 💻	Specification 📖	100
	Code 💻	Specification 📖	100
	Code 💻	Specification 📖	100

Useful Resources

Here are some relevant resources that one might find useful.

• Environment Setup (Mac, Windows, Linux): a tutorial on how to set up the development environment locally.
• Booksite: the booksite for Algorithms, 4th Edition (Sedgewick and Wayne, 2011).
• Code Repositories: the Java source codes in the lectures and in the book.
• edu.princeton.cs.algs4 Javadoc: the Javadoc for the edu.princeton.cs.algs4 package.