Data Structures and Algorithms are some of the most critical aspects of computer science and software engineering. This article explains what they are all about, why they are essential and how they can help create efficient solutions. Learning and understanding data structures as a developer helps you to understand technical problems on a deeper level and create logical and very efficient solutions.

We’ll be using Python in this article because of its easy-to-read syntax and once you can understand data structures and algorithms in Python, you’ll be able to apply it using any other language.

Prerequisite

To understand and be able to follow this guide, you need to understand the fundamentals of computer science and Python programming language’s syntax.

Overview of Data Structures and Algorithms

To fully explain these terms, I’ll take each separately and break them down.

What are Data Structures?

Data structures, in straightforward terms, are ways of managing and organising data. They are used to store and collect data which can be retrieved and modified at any time. They can also be used to keep track of information gotten from the user.

Data Structures can be in-built or user-defined. In-built data structures as the name suggests are created by the programming language’s developers and are available to everyone, examples are lists, tuples and dictionaries. Anyone creates user-defined data structures but can only be accessed by the person who created them. Examples are stacks, queues and trees. Each data structure has its specific use case but we won’t be going into that in this article.

What are Algorithms?

An algorithm is a step-by-step set of instructions designed to solve a specific problem or perform a task and it is often used in computer science and software engineering. It is used to modify information stored in data structures and use the modified information to perform tasks or solve problems. Commonly used algorithms are sorting and searching algorithms and they are used to detect, classify and compare information in various applications and websites.

Algorithms are first written in pseudocode so that the programmer can break down the process of solution, thinking of every step of the algorithm before the actual implementation and it also helps to correct the logic of the algorithm before converting to actual code. Now we have a better idea of what data structures and algorithms are and their importance to each other. To manipulate data stored in data structures, an algorithm must be applied.

Common data structures and algorithms

Arrays

An array is an ordered collection of items of the same data type stored in continuous and adjacent memory. It is not an in-built data structure, so to use it you’d have to import the array module. Importing the array module will also give you access to the available functions. Arrays can be used in sorting and organizing data in different orders.

Stacks

Stacks are linear data structures that utilize the Last-In-First-Out (LIFO) principle. This means that the last element added to the stack will be the first element to be removed from the stack. An example is a stack of dirty plates in the sink, the last plate added i.e. the first plate that is visible will be the first plate to be washed and removed from the stack. Stacks are used when applying the undo/redo functionality in text editors.

Queues

A queue is a linear data structure like a stack but it uses the First-In-First-Out principle instead. Elements added to the queue first will be the first to be removed i.e. elements are added to the back of the queue and are removed from the front of the queue. Queues can be used when handling hardware or real-time systems interrupts.

Trees

A tree is a data structure that consists of nodes connected by edges. It represents a hierarchal structure where every node has a parent and zero or more child nodes. Trees allow for efficient insertion and searching. They can be used to apply the navigation structure of a website or to implement decision-making in video games.

Sorting Algorithm

A sorting algorithm is used to arrange data in a particular way, it could be ascending or descending alphabetical, numerical or chronological order. There are different sorting algorithms namely quick sort, bubble sort, insertion sort and merge sort. Each sorting algorithm has its level of efficiency but the most efficient is quicksort. The type of sorting algorithm to be used will largely depend on the size of the dataset, the complexity of the data and the desired result. Sorting algorithms can be used to arrange items by price on an e-commerce website.

Searching Algorithm

Searching algorithms are used to locate specific a value from a collection of data such as a list or an array. Examples of searching algorithms are binary search, linear search and depth-first search. All these algorithms achieve the same but their level of efficiency differs, linear search goes through every item in the dataset until it finds the required value while binary search splits the dataset two multiple times until the value is found. Searching algorithms can be used to locate a keyword in a document or locate a contact in a contacts list.

Importance of Data Structures and Algorithms

Why are Data Structures and Algorithms so important?

• Effective Problem-solving: As a developer, having a firm understanding of Data Structures and Algorithms helps you to handle complex problems with relative ease, you’ll have the experience and skills needed to tackle such tasks and come up with efficient solutions. This is a very valuable skill when working with real-life applications.

• Optimized Performance: Understanding data structures and algorithms will give you the information needed to choose appropriate data structures and algorithms that will give the most efficient solution. This helps to save time and resources and increase the overall performance and responsiveness of the application.

• Technical interviews and coding assessments: Most technical job interviews test applicants on their critical thinking and problem-solving skills. Candidates who can solve problems more efficiently by using appropriate data structures and algorithms have a higher chance of passing the interviews.

Conclusion

Data structures and algorithms are essential aspects of computer science and software engineering as they help in creating efficient solutions. Understanding them properly will greatly improve the developer’s problem-solving skills, and ability to create efficient solutions that will optimize the performance of an application. If you’re interested in learning Data structures and algorithms, here’s a free course that I strongly recommend.