What Is Data Structure Basic Terminology of Data Structure?


Scott Campbell

When it comes to working with data in computer science and programming, understanding data structure is essential. Data structure refers to the way data is organized, stored, and accessed in a computer’s memory. It provides a framework for efficiently managing and manipulating data.

Basic Terminology of Data Structure:


Data refers to any piece of information that can be stored in a computer’s memory. It can be numbers, text, images, or any other form of digital information.

Data Element:

A data element is the smallest individual unit of data within a data structure. For example, in a list of names, each name would be considered a data element.

Data Type:

A data type defines the kind of value that a particular piece of data can hold. Examples of common data types include integers, floating-point numbers, characters, and strings.


An array is a collection of elements stored in contiguous memory locations. Each element in an array can be accessed using its index value.

Linked List:

A linked list is a linear collection of elements called nodes. Each node contains both the actual value and a reference to the next node in the sequence.


A stack is an abstract data type that follows the Last-In-First-Out (LIFO) principle. Elements are added or removed from only one end called the top.


A queue is an abstract data type that follows the First-In-First-Out (FIFO) principle. Elements are added at one end called the rear and removed from the other end called the front.


A tree is a hierarchical data structure composed of nodes. Each node can have zero or more child nodes, forming a branching structure.


A graph is a collection of nodes, also known as vertices, connected by edges. It represents relationships between different entities.


Hashing is a technique used to map data to a fixed-size array. It ensures efficient retrieval and storage of data by reducing the search time.


Sorting refers to arranging elements in a specific order, such as ascending or descending. It allows for efficient searching and retrieval of data.

In Conclusion:

Understanding the basic terminology of data structure is crucial for effective programming and problem-solving. It provides the foundation for designing efficient algorithms and organizing data in a way that maximizes performance. By familiarizing yourself with these concepts, you’ll be better equipped to tackle complex programming tasks and optimize your code.

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