Is BST a Data Structure or ADT?


Heather Bennett

Is BST a Data Structure or ADT?

A binary search tree (BST) is a data structure that allows efficient storing and retrieval of data. However, it can also be considered as an abstract data type (ADT). In this article, we will explore the nature of BST and discuss whether it should be categorized as a data structure or an ADT.

Data Structure vs. Abstract Data Type

Before diving into the specifics of BST, let’s first understand the difference between a data structure and an ADT.

A data structure refers to how data is organized, stored, and manipulated in memory. It defines the way data can be accessed and modified. Examples of data structures include arrays, linked lists, stacks, queues, trees, graphs, and more.

An abstract data type (ADT), on the other hand, refers to a high-level description of operations that can be performed on a particular set of data. It focuses on what operations are possible without specifying how they are implemented. An ADT provides an interface for interacting with the underlying data structure but does not concern itself with the implementation details.

The Nature of Binary Search Tree

A binary search tree is a hierarchical structure where each node has at most two children: a left child and a right child. The left child contains values smaller than its parent node while the right child contains values greater than its parent node.

The key characteristic of a BST is its ability to perform efficient search operations. By utilizing the binary search algorithm, we can quickly locate elements within the tree by comparing them with the values stored in each node.

Data Structure Perspective

  • From a data structure perspective, a BST is undoubtedly a valid classification. It provides a way to store and organize data efficiently, and its structure significantly influences the performance of operations.
  • The structure of the tree affects the time complexity of search, insertion, and deletion operations. A well-balanced BST ensures logarithmic time complexity for these operations.
  • Additionally, the implementation details such as node pointers and algorithms used for traversing the tree are essential aspects of its classification as a data structure.

Abstract Data Type Perspective

  • Considering the ADT perspective, a BST can also be seen as an abstract representation of a set of values with defined operations.
  • An ADT for a BST typically includes methods like insert, delete, search, minimum, maximum, inorder traversal, preorder traversal, and postorder traversal.
  • The ADT encapsulates the behavior and functionality of BST without specifying how it is implemented under the hood. This allows for interchangeable implementations that adhere to the same interface.


In conclusion, it is reasonable to classify a binary search tree both as a data structure and an abstract data type. From a data structure perspective, it provides an efficient way to store and manipulate data with specific implementation details. From an ADT perspective, it offers a high-level description of operations that can be performed on a collection of data without considering implementation specifics.

The classification of BST depends on the context in which it is discussed. Both perspectives are valid and provide valuable insights into understanding this powerful hierarchical data storage mechanism.

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