Dream of working at a MAANG company? Landing a job at one of these top-tier tech giants is the aspiration of many software engineers professionals. However, many fall short due to the incredibly rigorous coding interviews. These interviews are meticulously designed to filter out the best talent by not only testing your coding skills but also evaluating your problem-solving abilities, algorithmic knowledge, and efficiency in finding solutions.

This blog is a one-stop guide for software developers hoping to ace coding interviews. Here, we’ll explore some fundamental algorithms that are the key building blocks for coding interviews. By mastering these algorithms, you’ll showcase your problem-solving prowess, enhance your coding efficiency, and demonstrate your ability to think logically—qualities highly valued by hiring managers at top tech companies.

Today we will cover several important categories of algorithms (including sorting algorithms, searching algorithms, and more), and dive into 14 specific algorithms you'll need to know for your coding interview. These essential coding interview algorithms are:

Bubble sort

Selection sort

Insertion sort

Heap sort

Linear search

Binary search

Depth-first search (DFS)

Breadth-first search (BFS)

Merge sort

Quick sort

Dijkstra's algorithm

Huffman coding

Fractional knapsack problem

Dynamic programming

**Note:** *We will cover each of these algorithms and use cases in detail below.*

If you understand how these algorithms work and when to use them, you will be in great shape for your coding interviews at even the most prestigious tech companies.

Let's dive in!

## Importance of algorithms in coding interviews#

Understanding why algorithms are crucial in coding interviews is fundamental to your preparation. Algorithms are the backbone of problem-solving in computer science, and understanding them showcases the candidate’s ability to think logically, solve complex problems, and write efficient code.

### Why algorithms matter#

Algorithms are important because they:

**Test problem-solving skills: **Algorithms require you to break down problems into manageable parts, develop step-by-step solutions, and choose optimal approaches—mirroring real-world challenges in tech.

**Emphasize efficiency: **Understanding algorithms helps you write code that not only works but performs well. In the tech industry, efficient code can mean the difference between a product that scales and one that doesn’t. Interviewers look for candidates who can optimize their solutions to save time and resources.

**Demonstrate the breadth of knowledge: **Your familiarity with different algorithms shows your breadth of knowledge and ability to apply the right tool for the job. It reflects your readiness to handle a variety of tasks that you might encounter on the job.

## Real-world applications#

Algorithms aren’t just theoretical concepts; they have practical applications across various tech domains. For instance, search algorithms like binary search are used by digital catalogs to search and retrieve information about particular items in the database. Sorting algorithms like merge sort power recommendation systems that suggest relevant products or content to you based on your preferences. By understanding these algorithms, you gain valuable insight into how tech giants handle data and solve complex problems behind the scenes.

Understanding the significance of algorithms in coding interviews and their real-world applications prepares you for technical challenges and provides insights into how industry leaders solve intricate problems. This foundational knowledge is significant for excelling in coding interviews and pursuing careers at top-tier tech companies.

## Must-know algorithms#

Now that we understand why algorithms are crucial in coding interviews and how they apply to real-world scenarios, let’s dive into the specific algorithms you need to know to ace your coding interviews. We’ll cover essential algorithms across various categories, including sorting, searching, tree algorithms, dynamic programming, and more. By the end of this section, you’ll have an understanding of the algorithms that are commonly tested in interviews and how to solve problems using them.