If you're a big Harry Potter fan, you probably enjoyed the Triwizard Maze. When racing through the maze, the competitors were faced with decisions about which path to take. Modeling these choices can be done using a tree data structure.

Waiting in a line—or as the British call it, “queueing”—is a literal visualization of a queue data structure. The first person in line is the first person who gets whatever they’re waiting for and leaves the line.

When you fill a PEZ dispenser, you push the candy from the top down. When you eat the candy, you pop a piece off the top of the literal stack of pieces. A stack data structure behaves the same way.

Code challenges should be representative of the work a candidate will do for the role they are applying for. Rewriting code challenges to fit a role is a lot of work, but here's a step by step guide to simplify it.

Developers spend between 50% and 75% of their coding time debugging. Becoming a faster debugger would free up a lot of time for more challenging problems. Here are 6 strategies for speeding up your debugging time.

A scavenger hunt is a physical representation of a linked list. A linked list is a data structure characterized by sequential data access and no random access.

Recursion has a reputation in computer science of being intimidating but what is it exactly? Russian nesting dolls are a great metaphor for recursion so let's use them as an example to break it down in an easy-to-understand way.

Intentional relationship building is an important part of being a successful manager. You support people achieving their goals and pushing their career forward. The first 1:1 with a new report is a great time to be intentional and set the tone for your relationship.

Venn diagrams are a great way to think about set theory. In this post, we'll use Venn diagrams to see how our Instagram feed would change based on various set theory operations.

When you cooking with ratios, the amount of ingredients you need changes in proportion to how much of the food you want to make. Big O notation measures the relative complexity of a function or algorithm in proportion to the size of the function’s input.