Data Structures in Computer Science
Data Structures in Computer Science
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Data structures are organized ways of storing and accessing data in a computer's memory, so that they can be used efficiently in various algorithms and applications. Data structures can range from simple arrays and linked lists, to more complex structures like trees, graphs, and hash tables, each with their own specific advantages and use cases. The choice of an appropriate data structure depends on the specific requirements of a given problem and the desired time and space complexity of the solution.
Arrays
An ordered collection of elements stored in contiguous memory locations,
accessed using indices.
Linked Lists
A linear data structure where each element points to the next element in the list.
Stacks
A last-in, first-out (LIFO) data structure, where elements are pushed onto and popped off the top of the stack.
Queues
A first-in, first-out (FIFO) data structure, where elements are added to the back and removed from the front.
Trees
A hierarchical data structure where each node has a parent and child nodes, with the exception of the root node which has no parent.
Graphs
A non-linear data structure made up of nodes and edges, representing relationships
between elements.
Hash Tables
A data structure that stores key-value pairs, allowing for fast and efficient lookup using the keys.
Tries
A tree-based data structure that is optimized for searching through large sets of strings.
Heaps
A complete binary tree data structure where the parent node is always greater or smaller than its children, depending on the type of heap.
Matrices
A two-dimensional data structure that stores elements in rows and columns.
Bloom Filters
A probabilistic data structure that is used to test whether an element is a member of a set.
Skip Lists
A linked list data structure with multiple levels, allowing for faster search times compared to traditional linked lists.
Strings
A string is a sequence of characters. In computer science, strings are often used to represent text, such as words, phrases, or sentences.
Data structures, at a high level, are techniques for storing and organizing data that make it easier to modify, navigate, and access. Data structures determine how data is collected, the functions we can use to access it, and the relationships between data.
Data structures are used in almost all areas of computer science and programming, from operating systems to basic vanilla code to artificial intelligence.
Data structures enable us to:
Manage and utilize large datasets
Search for particular data from a database
Design algorithms that are tailored towards particular programs
Handle multiple requests from users at once
Simplify and speed up data processing
Data structures are vital for efficient, real-world problem solving. After all, the way we organize data has a lot of impact on performance and usability. In fact, most top companies require a strong understanding of data structures.
Anyone looking to crack the coding interview will need to master data structures.
JavaScript has primitive and non-primitive data structures. Primitive data structures and data types are native to the programming language. These include boolean, null, number, string, etc.
Non-primitive data structures are not defined by the programming language but rather by the programmer. These include linear data structures, static data structures, and dynamic data structures, like queue and linked lists.
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