Why Tree Is Called Recursive Data Structure?


Larry Thompson

Why Tree Is Called Recursive Data Structure?

A tree is a hierarchical data structure that consists of nodes connected by edges. It is called a recursive data structure because it can be defined in terms of itself. In other words, a tree can contain subtrees, which are smaller trees within the main tree.

What is Recursion?

Recursion is a programming concept where a function calls itself to solve a problem. This technique allows us to break down complex problems into simpler subproblems that can be solved using the same logic.

In the case of trees, each node can have zero or more child nodes. These child nodes themselves can be trees with their own child nodes, and so on. This recursive nature of trees makes them well-suited for representing hierarchical relationships.

The Structure of Trees

A tree consists of nodes and edges. The topmost node is called the root node, and it serves as the starting point for traversing the tree. Each node in a tree can have any number of child nodes.

To better understand the structure of trees, let’s take a look at an example:

      / | \
     B  C  D
       / \
      E   F

In this example, ‘A’ is the root node, and it has three child nodes: ‘B’, ‘C’, and ‘D’. Node ‘C’ has two child nodes: ‘E’ and ‘F’.

Recursive Operations on Trees

The recursive nature of trees allows us to perform common operations efficiently:

  • Traversal: We can traverse a tree using various algorithms such as pre-order, in-order, and post-order traversal. These algorithms visit each node of the tree, including the child nodes recursively.
  • Search: We can search for a specific node or value in a tree by recursively searching through its child nodes.
  • Insertion: We can insert a new node into a tree by finding the appropriate position based on certain criteria and recursively inserting it as a child node.
  • Deletion: We can delete a node from a tree by recursively searching for the desired node and reorganizing the remaining nodes accordingly.


Trees are called recursive data structures because they can be defined in terms of themselves. The recursive nature of trees allows for efficient traversal, searching, insertion, and deletion operations. By understanding and utilizing the power of recursion, we can effectively work with trees in various applications.

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