Introduction to Data Structures

This set of flashcards covers key vocabulary and concepts related to data structures, including definitions, characteristics, operations, and applications.

Data Structure

A systematic way of organizing, managing, and storing data for efficient access and modification.

Primitive Data Structures

Basic structures provided by programming languages, including integer, float, character, Boolean, and Pointer.

Non-Primitive Data Structures

Data structures derived from primitive types, categorized into linear and non-linear.

Linear Data Structure

A data structure where elements are arranged in a sequential order and each element is connected to its next.

Non-Linear Data Structure

A data structure where elements are not arranged sequentially but are connected in a hierarchical or network manner.

Traversal

Accessing each element of a data structure exactly once.

Insertion

Adding a new element to a data structure.

Deletion

Removing an existing element from a data structure.

Searching

Finding an element by value or position in a data structure.

Sorting

Arranging elements in a specific order within a data structure.

Merging

Combining two or more data structures.

Characteristics of Primitive Data Types

Indivisible atomic nature, direct machine representation, fixed memory size, efficient operations, and static nature.

Dynamic Nature (Non-Primitive)

The ability of certain data structures to change size at runtime.

Memory Allocation (Primitive)

Primitive variables generally allocated in stack memory for faster access.

Complexity of Implementation

Linear data structures are easier to implement than non-linear data structures.

Choosing the Right Data Structure

Choosing a data structure based on the type of data, frequency of operations, memory constraints, and performance requirements.

Real-World Applications

Examples of data structures used in various fields, such as stacks in compiler design and graphs in networking.