In mathematics and data structures:

It is an acyclic graph that includes hierarchically structured nodes in a *"top to bottom"* fashion.

A tree's top is called the root node where other nodes branch off and become parent nodes to other nodes

(i.e. they are in *"higher order"* than their child nodes).

Each child node can only have *one* parent node.

A node not having any child nodes (and thus being an end-point) is called a *leaf.*

The maximum number of children a node can have is called *the order of the tree.*

The maximum iterations needed to reach a desired leaf in the tree is called *the depth of the tree.*

When every node in a tree has the same order and every leaf the same depth, the tree is *balanced*.

A tree may have varying number of children per node, and data storage can be accomplished within different depths throughout the tree.

Such a tree structure is characterised an *asymmetrical or unbalanced tree.*

Tree structures are heavily used in several computing practices, from databases (B-trees for faster data processing)

to 3-D First-person shooter games (BSP trees, which help calculate the world the player sees).