When preparing for an interview, computer programmers may need to review the different types of data structures. A data structure is a way of managing and organizing data effectively to help in the retrieval process. Understanding how data structures work can demonstrate to employers that you understand the fundamentals of programming.
In this article, we discuss data structures, explain why they’re important, and provide a list of nine types of data structures every programmer should know.
What is a data structure?
A data structure is a method for organizing and storing data in computers. It represents a collection of data values, the relationships between those values and the operations or functions they can deliver. Computer programmers use data structures to pass data to other components of an application or to a completely new application. The four primary functions of data structures are inputting, processing, maintaining, and retrieving data.
Why are data structures important?
Data structures are an important component of computer science since they help professionals store and manage large datasets. Using an effective system can help you retrieve information easily. Employers often ask individuals about data structures in computer science interviews to showcase their knowledge of the fundamental starting point for programming. It’s also helpful for other related sectors, such as artificial intelligence (AI), graphics and operating systems.
9 types of data structures
There are a variety of data structures that computer programmers can use depending on the task they are completing or the application they’re using. Here are nine common types of data structures you can use in software engineering:
Arrays store similar items together. This structure uses contiguous memory allocation to organize data. Those using an array identify each element with at least one array index or key. An array serves as the foundation for other data structures, such as hash tables and lists. Computer scientists often use this structure when sorting algorithms.
Stacks use a last in, first out (LIFO) structure where the computer orders previous work with the last action appearing first. For instance, if you enter the dataset, “1, 2, 3, 4,” the last digit, “4,” would appear at the top. This type of data structure creates a pile or stack of information. A stack data structure is helpful when organizing information where the order of actions is important. The design of this structure helps you make sure you complete your task before moving on to a new one.
Contrary to stacks, queues follow a first in, first out (FIFO) structure for organizing data. This linear structure resembles a queue for waiting since information goes in and waits to be outputted. The information entered first is the first to leave the line. Computer programmers use queues to organize data that doesn’t need to be processed immediately.
4. Linked lists
Linked lists organize items, or nodes, in linear order based on those related to each other. Each node consists of the data and a pointer. The data is what the programmer assigned to the node, and the pointer is a reference to the next node in the series. Linked lists work well for situations where you need to be able to delete data. They also can also help implement stacks and queues.
5. Binary trees
A binary tree is a non-linear structure that consists of nodes with two potential values or directions. The top node, or root, contains a right child and a left child. The different types of binary trees include:
Rooted binary tree: Rooted binary trees have a root node, with every node having up to two children.
Full binary tree: This type of binary tree occurs when every node has either zero or two children.
Perfect binary tree: In a perfect binary tree, all interior nodes contain two children, and all external nodes, or leaves, have the same level.
Complete binary tree: Complete binary trees occur when all levels except for the last are completely filled and nodes are located as far left as possible.
Balanced binary tree: Balanced binary trees are ones where the left and right children’s heights are different by at least one, the left child has a balanced amount and the right child has a balanced amount.
Degenerate tree: In a degenerate tree, each parent node only has one child, representing a linked list.
Binary trees are helpful when reflecting structural relationships in data. They can also help represent hierarchies.
Graphs are a type of nonlinear list used to represent a network. They consist of nodes and edges that connect to one another. These structures use a pair, X and Y, with the X vertex connecting the Y vertex. Graphs are useful when studying a network, such as a path in a city or a social media network.
Tries, or “prefix trees” are tree-like data structures used to store data. They are often used to represent words of the alphabet. Nodes of the tree are strings programmers can retrieve by going down the branch. Tries are useful for organizing data dependent on a prefix of a string. A common use for tries is providing auto-suggestions and looking up words in a dictionary.
8. Hash tables
Hash tables, or maps, store key-value pairs. They compute an index, or hash code, into slots where the desired value is located. Computer programmers store information in an array manner. They can use hash tables to implement associate arrays, database indexes, and the set data structure.
9. Skip lists
Skip lists are probabilistic data structures that list elements with a linked list. This type of structure is called a skip list because it skips several elements of an entire list. Each additional level in a skip list contains fewer elements, with no new elements. Skip lists are helpful for instances when programmers want to remove, insert, and search for information quickly.
I hope you find this article helpful.