68. Data Structure
Data structures refer to the way data is organized and stored in computer systems. It's a critical concept in computer science as it allows for efficient data manipulation, retrieval, and storage. Data structures can be broadly classified into two categories: primitive and non-primitive.
Primitive data structures include simple data types such as integers, floats, and characters. These data types are built into programming languages and have fixed sizes, making them relatively easy to use and manipulate.
Non-primitive data structures, on the other hand, are more complex and require a more nuanced approach to their use. They can be further categorized as linear or nonlinear data structures.
Linear data structures, as the name suggests, store data in a linear sequence, where each element has a predecessor and successor. Examples include arrays, linked lists, and stacks. Arrays are a type of data structure that stores a fixed number of elements of the same data type. Linked lists, on the other hand, are a dynamic data structure that can store an arbitrary number of elements and are made up of nodes that contain the data and a reference to the next node. Stacks are a type of linear data structure that uses the Last-In-First-Out (LIFO) principle, meaning the last element added is the first to be removed.
Nonlinear data structures, on the other hand, store data in a hierarchical or tree-like structure, where each element has one or more children. Examples include trees, graphs, and heaps. Trees are a type of data structure that consists of a root node, branches, and leaves. Graphs are a collection of nodes connected by edges and can be directed or undirected. Heaps are a specialized tree-based data structure that allows for efficient retrieval of the maximum or minimum element in constant time.
In conclusion, data structures are an essential concept in computer science, and understanding their use and implementation is critical for efficient programming and algorithm design.