Trees & Tries

Trees and tries are the tree-shaped corner of Spotify's coding surface, and the two traversals behind them, DFS and BFS, recur across the whole loop. Spotify tends to frame them in product language: walk a playlist-folder hierarchy, follow user-to-content links, find a path in the artist graph. The trie shows up somewhere more specific, the search box that completes a track or podcast name as you type. Underneath both sits standard binary-tree and prefix-tree material, run live on CoderPad and tested against real inputs.

Treat this cluster honestly. There is no signature algorithm here. Trees are a smaller slice of the loop than the hashing and sliding-window clusters. What you get is the usual tree-and-trie spine pointed at Spotify's product surfaces: Max Depth shows up as folder depth, autocomplete as the search bar. The actual work is narrow. Drill the two templates that fold almost every problem in this space into a few lines. Then prove them on one tree problem and one trie problem you can run and narrate.

The Spotify angle

One recursion shape answers most binary-tree prompts here, so name what each node hands its parent before you reach for a global variable. The shape is a depth-first helper that returns a single fact about the subtree below it. A value held outside the recursion absorbs the answer that spans both sides. Maximum Depth, the recurring easy starter, returns the taller branch plus one. Diameter returns that same depth while an outer maximum watches the path that turns at a node. Validate-BST hands up an allowed value range. Lowest common ancestor reports whichever child found a target. Narration counts here, more than raw speed. So say the return value out loud, "this helper returns the subtree depth," before you write a line of the helper.

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