The ultimate guide to recursion interviews with strategies developed by FAANG engineers. Practice with real-world interview questions, detailed explanations, and visualizations to prep faster.

If you’ve got an interview coming up and want to brush up on your knowledge, or if you’ve ever struggled with solving coding problems using recursion, you'll find this course helpful.
 
You’ll start with the basics of what recursion is and why it’s important before diving into what it looks like in practice. You’ll see how recursion can help you solve a variety of different math, string, and data structure problems by using interactive code playgrounds that you can execute directly in your browser. You’ll have access to detailed explanations and visualizations for each problem to help you along the way.  
 
By the time you’re done, you’ll be able to use what you’ve learned to solve complex real-world problems and even advance more easily through your interviews at top tech companies.

Recursion for Coding Interviews in Java

## What is Depth First Search?

**Depth First Search** is a method used to traverse and search all nodes in a graph. The algorithm allows us to determine if two nodes, node a and node b, have a path between them. This process starts from the **root node** and then traverses all through that **branch** until it reaches the **leaf**, the last node with no other children, and then **backtracks**. This continues until all nodes have been traversed. The illustration below explains the process of `DFS` in a directed graph. 

## Implementing the Code

The code below shows how to implement this process using recursion. First, let’s examine the code, and then we will move on to its explanation.

You must modify the edges by using `addEdge`, and the number of vertices `nVertices` to create your own graph, `g`.Then, run `DFSRecursion` on these variables.

# What is Depth First Search?

**Depth First Search** is a method used to traverse and search all nodes in a graph. The algorithm allows us to determine if two nodes, node a and node b, have a path between them. This process starts from the **root node** and then traverses all through that **branch** until it reaches the **leaf**, the last node with no other children, and then **backtracks**. This continues until all nodes have been traversed. The illustration below explains the process of `DFS` in a directed graph. 

# Implementing the Code

The code below shows how to implement this process using recursion. First, let’s examine the code, and then we will move on to its explanation.

You must modify the edges by using `addEdge`, and the number of vertices `nVertices` to create your own graph, `g`.Then, run `DFSRecursion` on these variables.

This lesson will teach you how to write a recursive code for depth-first search in graphs.

Fundamentals of Recursion

Iteration to Recursion

Recursion with Numbers

Recursion with Strings

Recursion with Arrays

Recursion with Data Structures

Depth First Search in Graphs

What is Depth First Search?

Implementing the Code