We use Dijkstra's algorithm to find the shortest path from one node to another in a complicated house-shaped graph. Also, Vaidehi sings us a song.

To get from one point to any other point in a graph, make Dijkstra your weapon of choice.

DAG-nabbit! Don't forget to check whether or not a graph is a directed acyclic graph.

Traversing through a graph is pretty edgy.

To go about coding the depth-first search algorithm (DFS), we revisit an old friend: adjacency lists.

When going through a maze, hitting a dead end isn't always a bad thing, especially in depth-first search (DFS).

Take a deep breath as we dive into breadth-first search, a super nifty graph traversing algorithm, which gives the shortest way to get from one node to another.

Adjacency lists are the new type of hybrid you're going to want to be driving around your code.

We tackle representing graphs and the parts that make it up.

You won't want to miss the buzz about b-trees, the general version of a 2-3 tree, and a super efficient data storing tree structure.