My solutions to the Princeton Algorithms Courses: Algorithms, Part I and Algorithms, Part II programming assignments on Coursera.
Each project directory comes with the following items:
- Java source code: these are the code submitted to the AutoGrader
Makefile
: which provides 2 routinesmake submit
: which will compress the Java source code into a.zip
inout/
for submitting to the AutoGradermake clean
: remove directoryout/
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.
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 |
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 theedu.princeton.cs.algs4
package.