Data structures can be classified based on different criteria, such as the way they store and organize data, the type of operations they support, and their usage in various applications. Here are some common ways of classifying data structures:
Based on data storage and organization:
- Arrays: a collection of elements of the same data type stored in contiguous memory locations
- Linked Lists: a collection of nodes, each containing data and a reference to the next node in the list
- Trees: a hierarchical structure consisting of nodes with parent-child relationships
- Graphs: a collection of vertices and edges that represent connections between them
- Hash Tables: a data structure that stores key-value pairs and uses a hash function to map keys to indexes in an array
Based on data access:
- Sequential: elements are accessed in a sequential order, such as arrays and linked lists
- Random: elements can be accessed randomly, such as hash tables and binary search trees
- Based on operations:
- Search: data structures that support efficient searching, such as binary search trees and hash tables
- Sort: data structures that support efficient sorting, such as heaps and merge-sort trees
- Insertion and deletion: data structures that support efficient insertion and deletion of elements, such as linked lists and binary search trees
Based on usage:
- Linear: data structures that store data in a linear fashion, such as arrays and linked lists
- Non-linear: data structures that store data in a hierarchical or network-like structure, such as trees and graphs
- Primitive: data structures provided by programming languages, such as integers, floats, and booleans
- Composite: data structures that are composed of primitive data types or other data structures, such as arrays and records
It's important to choose the appropriate data structure based on the problem requirements and the type of operations that will be performed on the data. Understanding the classification of data structures can help in selecting the right data structure for a given problem.
