In our season finale, we're wrapping up our sorting algorithm classifications with two final categories: recursive vs. non-recursive and comparison vs. non-comparison. And we throw in some tomatoes, just for good measure.

What does it mean for a sorting algorithm to be "stable"? What about it being internal or external? We explore two more ways to classify sorting algorithms with the help of a few Michaels.

What's a sorting algorithm, and how do we categorize them? We dig into the six ways to classify them and explore why they're so important.

Sets are everywhere, and you're probably already working with them! We talk about how they're actually implemented and how well they perform.

If you know about venn diagrams, then you basically know set theory! We explain how the two are related and connect it back to computer science with the help of some of our favorite foods.

The Brians still need their own tables! We resolve our collision with a new strategy: chaining.

What do you do when you're in a hash table, and two pieces of data get assigned the same spot?! You've got a collision, and you need a resolution! We dig into one strategy to resolve a collision, and make sure each data has a spot.

In our intro to hash tables, we use books, pizza toppings, and fridge operators to break down how hash tables work and what makes them so awesome.

How does breadth-first search actually work? And how do you know whether you should use that, or depth-first search? And what's the Big O notation for BFS anyway? Let's find out!

We are getting in line, or enqueuing, for breadth-first search! We walk through the steps and compare the process to depth-first search.