# Trees & Binary Search Trees

A file system has folders inside folders. An org chart has a CEO with reports, who have their own reports.
An HTML page has elements nested inside elements. All three are the same shape wearing different clothes:
a **tree** - and once you can see that shape, a whole category of real code stops looking mysterious.

This guide starts with what a tree actually is, then narrows to one specific, hugely useful kind: the
**binary search tree**, which turns the ordering trick from
[Sorting & Searching, Explained](/guides/sorting-and-searching-explained) into a data structure you can
insert into and search on the fly.

## How to read this

Read in order - Phase 2's binary search tree only makes sense once "node," "child," and "leaf" from Phase 1
are second nature.

## The phases

1. **[What a Tree Is](01-what-a-tree-is.md)** - nodes, root, children, leaves, and why so many real-world
   structures turn out to be trees.
2. **[Binary Search Trees](02-binary-search-trees.md)** - the one ordering rule that makes a tree fast to
   search and insert into, with real code building one from scratch.
3. **[BST Performance & Gotchas](03-bst-performance-and-gotchas.md)** - why a BST is usually `O(log n)`,
   how it can silently degrade to `O(n)`, and what fixes that.