The ultimate recursion guide! Master basics, solve real-world problems, and get interview-ready in hours with FAANG engineers’ proven strategies.

If you’ve ever struggled with solving coding problems using recursion, or if you need to brush up your recursion skills for an interview, this course is for you! We will start with the basics of recursion before we practice solving actual coding problems. You’ll have access to detailed explanations and visualizations for each problem to help you along the way.

By the time you have completed this course, you’ll be able to use all the concepts of recursion to solve complex, real-world problems. We hope that this course will help you ace all the recursion related questions during interviews at top tech companies!

Recursion for Coding Interviews in Python

# Solution: Using Recursion
The following solution sorts the array **recursively**. This process is commonly known as the **Bubble sort algorithm**.

def sort(testVariable, length):
	# Base case
	if length <= 1 :
		return
	
	# Recursive case
	# Sort first n-1 elements
	sort(testVariable, length - 1)

	# Insert last element at its correct position in sorted array
	lastElement = testVariable[length - 1] # fetch the last element
	temp = length - 2 # start finding its correct location from one element before it
	
	# Move elements of testVariable[0..i-1], that are greater than key, to one position ahead of their current position 
	while temp >= 0 and testVariable[temp] > lastElement:
		testVariable[temp + 1] = testVariable[temp]
		temp = temp - 1

	testVariable[temp + 1] = lastElement # place the element in its correct position


# Driver Code
testVariable = [5, 4, 2, 3, 1]
print("Original Array ---> " + str(testVariable))

sort(testVariable, len(testVariable))
print("Modified Array ---> " + str(testVariable))

## Explanation

In the code snippet above, we reduce the `length` of the input array `testVariable` in each **recursive call**. When the `length` reaches $1$, we `return` since an array of size $1$ is already sorted. This is also our **base case**. When the **child** recursive call returns, we place the last element that has been reached into its correct position.

> Important note: we traverse the array from the right side to the left side.

This review provides a detailed analysis of the solution to sort an array.

Recursion Fundamentals

Iteration Vs. Recursion

Recursion with Numbers

Recursion with Strings

Recursion with Arrays

Recursion with Data Structures

Conclusion

Solution Review: Sort an Array

Solution: Using Recursion