Is Disjoint Set an Abstract Data Type?


Larry Thompson

The disjoint set data structure is a fundamental concept in computer science that allows us to efficiently solve problems involving partitioning a set into subsets. But is the disjoint set an abstract data type? Let’s explore this question in detail.

What is an Abstract Data Type?

An abstract data type (ADT) is a high-level description of a set of operations that can be performed on a data structure, without specifying the implementation details. It defines the behavior and properties of the data structure, allowing us to focus on how to use it rather than how it works internally.

ADTs provide an abstraction layer, making it easier for programmers to understand and use complex data structures by hiding unnecessary details. Common examples of ADTs include stacks, queues, lists, and trees.

Disjoint Set Data Structure

The disjoint set data structure, also known as the union-find or merge-find data structure, is used to efficiently manage a collection of disjoint sets. Each element in the set is represented as a separate node in the disjoint set forest. The elements within each set are connected by parent-child relationships.

The main operations supported by the disjoint set are:

  • MakeSet(x): Creates a new singleton set with element x.
  • Find(x): Returns the representative (root) element of the set containing x.
  • Union(x, y): Merges two sets containing elements x and y into a single set.

Is Disjoint Set an Abstract Data Type?

The disjoint set can be considered an abstract data type because it provides a well-defined interface (the aforementioned operations) that hides its internal implementation details. Users can utilize these operations to manipulate the sets without needing to know how the sets are actually represented or connected internally.

The disjoint set abstract data type allows us to solve a wide range of problems efficiently, such as finding connected components, detecting cycles in graphs, and implementing Kruskal’s algorithm for minimum spanning trees.

Example Usage:

Let’s consider an example to illustrate the usage of disjoint sets. Suppose we have a set of 6 elements: {A, B, C, D, E, F}. Initially, each element is in its own separate set:


Now let’s perform some union operations:

Union(A, B)
Union(C, D)
Union(E, F)

After these union operations, we have three sets: {A, B}, {C, D}, and {E, F}.

We can also find the representative elements of each set using the Find operation:

Find(A) -> returns B
Find(C) -> returns D
Find(E) -> returns F

This example demonstrates how we can use the disjoint set abstract data type to efficiently manage sets and perform operations on them.


The disjoint set data structure is indeed an abstract data type. It provides a high-level interface that allows us to manipulate sets without worrying about implementation details. By utilizing this powerful ADT, we can efficiently solve various problems involving partitioning and merging sets.

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