Why Is Tree Called a Recursive Data Structure?


Angela Bailey

Why Is Tree Called a Recursive Data Structure?

A tree is called a recursive data structure because it is defined in terms of itself. Just like a real-life tree branches out into smaller branches and leaves, a tree data structure consists of nodes that are connected in a hierarchical manner.

What is Recursion?

Recursion is a programming technique where a function calls itself to solve a problem. It breaks down complex problems into smaller, more manageable subproblems.

In the context of trees, recursion plays a fundamental role in their definition and traversal.

The Structure of a Tree

A tree consists of nodes connected by edges. The topmost node is called the root, and each node can have zero or more children. Nodes without any children are called leaves.

The connection between nodes forms the hierarchical relationship. Each child node is linked to its parent node, creating a parent-child relationship throughout the tree.

An Example:

  • Root: Node A
  • Children: Node B, Node C, Node D
  • Leaves: Node D, Node E

The Recursive Nature of Trees

Trees exhibit recursive properties because each child node can be considered as the root of its own subtree. This concept allows us to break down complex tree problems into smaller subproblems that can be solved using similar techniques.


To calculate the total number of nodes in a tree, we can use recursion. The base case would be a tree with no nodes, which would have a count of 0. For a tree with nodes, we sum the count of the current node and the counts of its children (subtrees).

By recursively applying this logic to each child node, we can traverse the entire tree and calculate the total number of nodes.

Traversal Techniques

Recursion is also widely used in tree traversal algorithms. There are three common strategies for traversing trees:

  • Preorder Traversal: Visit the current node, then recursively visit its left subtree, followed by its right subtree.
  • Inorder Traversal: Recursively visit the left subtree, then visit the current node, followed by recursively visiting the right subtree.
  • Postorder Traversal: Recursively visit the left subtree, then recursively visit the right subtree, followed by visiting the current node.

All of these traversal techniques employ recursion to traverse through each node and perform operations or gather information as required.

In Conclusion

Trees are called recursive data structures because they exhibit recursive properties. The hierarchical nature of trees allows them to be defined in terms of smaller subtrees and solved using recursive techniques. Recursive functions play a crucial role in defining and traversing trees efficiently.

Understanding recursion and how it applies to tree structures is essential for any programmer or computer science enthusiast.

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