computer-science-in-javascript
Collection of classic computer science paradigms, algorithms, and approaches written in JavaScript.
A teaching collection of classic computer science data structures and algorithms written in plain, heavily-commented JavaScript, paired with blog post explanations designed for people learning these concepts for the first time.
This repository is a companion to a series of educational blog posts written by Nicholas C. Zakas, a well-known JavaScript author. It contains JavaScript implementations of classic computer science concepts: data structures like linked lists and binary search trees, sorting algorithms like bubble sort and selection sort, and other foundational algorithms like binary search and base64 encoding.
The purpose is educational. The code is deliberately written to be easy to follow rather than as concise as possible, and the README notes that heavy commenting is intentional to help people who are new to these concepts. Each implementation pairs with a blog post on the author's website that walks through the reasoning behind it.
The repository has two layers of content. The original implementations go back to a 2009 blog post series and sit in folders named data-structures, algorithms, and encodings. A newer batch of implementations, started in 2019 and updated to use modern JavaScript features, lives in the src folder. The author is gradually replacing the old versions with updated ones, so the two sets coexist during that transition.
Running the code requires Node.js version 8 or later. Setup is the standard pattern for a JavaScript project: clone the repository, run the install command to pull in dependencies, then run the test command to verify everything works.
The project is maintained as a teaching resource tied to the blog post series, so only bug fixes are accepted. No new features are being added. The license is MIT, which allows free use for any purpose. Anyone learning JavaScript who wants to see how these fundamental data structures and algorithms work, with clear step-by-step code and accompanying written explanations, will find this useful.
Where it fits
- Learn how linked lists, binary search trees, and sorting algorithms work by reading plain, step-by-step JavaScript code.
- Use the implementations as study material alongside the author's blog posts that explain the reasoning behind each one.
- Run the included tests to verify your understanding as you work through each data structure or algorithm.