Big-O Notation Cheat Sheet
This cheat sheet shows the Big-O time and space complexities (runtime analysis) of common algorithms used in the computer science field. You can see which collection type or sorting algorithm to use at a glance to write the most efficient code. This is also useful for those studying Computer Science in University or for technical interview tests where Big-O notation questions can be fairly common depending on the type of company you are apply to.
Knowing how to write efferent code using Big-O notation will help you prevent accumulating technical debt and can save you time and money in the long run. Perfect gift for your programming student or friend.
This quick guide cheat sheet gives the time and space complexity for the following data structures:
- Basic Array
- Dynamic Array
- Singly-Linked List
- Doubly-Linked List
- Skip List
- Hash Table
- Binary Search Tree
- Sorted Array Using Binary Search
- Cartesian Tree
- Splay Tree
- Red-Black Tree
- AVL Tree
In addition to giving the time and space complexity this cheat sheet also has links to the data structures so you can learn more about how they work and are implemented beyond the runtime analysis!
Every Software Engineer Needs A Solid Understanding Of Runtime Analysis
All the big companies are going to test your knowledge on Big O notation and your runtime analysis skills. It’s more than a mental flex, writing performant code is critical when you are building systems that will support millions and billions of clients. Put yourself in a position to stand out by studying and grasping Big O notation. Not only will you stand out to employers, but your personal projects will improve as well. With this cheat sheet in your arsenal you can be confident that you are on the right track to becoming a master software engineer. The path and the journey begins with you, start today!