# Which Data Structure Is Used by Map in STL?

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Scott Campbell

The map is a widely used data structure in the Standard Template Library (STL) of C++. It provides an efficient way to store and retrieve key-value pairs. But have you ever wondered which data structure is used by the map in the STL?

The answer lies in a balanced binary search tree called Red-Black Tree. The Red-Black Tree is a self-balancing binary search tree that guarantees a logarithmic time complexity for operations like insertion, deletion, and search.

## Why Use a Red-Black Tree?

The choice of using a Red-Black Tree for implementing the map data structure is not arbitrary. It offers several advantages:

• Balanced Structure: The Red-Black Tree‘s balancing properties ensure that the height of the tree remains logarithmic. This balance ensures that operations on the map have consistent performance, even with varying input sizes.
• Faster Operations: With logarithmic time complexity for common operations like insertion, deletion, and search, the Red-Black Tree provides fast and efficient access to key-value pairs.
• Simplicity: Although the underlying implementation of a balanced binary search tree can be complex, using it through the map interface simplifies its usage. As a developer, you don’t need to worry about managing tree rotations or maintaining balance manually.

## The Red-Black Tree Properties

A red-black tree follows specific properties that ensure its balanced structure:

1. Binary Search Tree Property: Like any binary search tree, the left child of a node contains a smaller value, while the right child contains a larger value. This property allows efficient search, insertion, and deletion.
2. Red-Black Property: Each node in the tree is colored either red or black.

The color of the root node is always black. Additionally, no two adjacent nodes can be red; if a node is red, its children must be black.

3. Black Depth Property: The black depth of a node refers to the number of black nodes encountered while traversing from that node to any leaf. All paths from the root to leaves must have an equal number of black nodes.

## Operations on Map

The map provides various operations to manipulate key-value pairs:

• Insertion: When inserting a new key-value pair into the map, it uses the Red-Black Tree’s properties to maintain balance and order.
• Deletion: Removing a key-value pair from the map also ensures that the Red-Black Tree remains balanced by performing necessary rotations and recoloring.
• Search: Searching for a specific key in the map utilizes the binary search tree property of the Red-Black Tree for efficient retrieval.

## In Conclusion

The choice of using a Red-Black Tree as the underlying data structure for implementing the map in STL is crucial for its efficiency and performance. By maintaining balance through its red-black properties, it provides fast operations with consistent time complexity. As developers, we can leverage this powerful data structure without worrying about the intricate details of its implementation.