Recursion refers to a process that repeats itself until it has achieved its goal. This process repeats itself in terms of its own updated version. Commonly, when a process repeats itself, it is called Recursion.
 Programming Definition
 Importance of Recursion
 Use of Recursion
 How Recursion operates
 Example Functions
Programming Definition
In computer science, one has to work with finding optimal solutions to problems that occurred. These problems could range from a simple calculation to building a fullfledged project. For this, computer scientists usually break more significant problems into small portions. Then, they solve those problems to get the final result at the end. Recursion is known to solve small instances of the problem and provide the solution efficiently.
Importance of Recursion
Comparison with loops and iterations
Usually, programmers use iterations to solve programming problems. Iteration means generating a sequence of outcomes. Programmers prefer it to solve a problem where they can find the solution after a few iterations. However, when it comes to solving enormous problems, Recursion plays a vital role in providing a solution in a short time.
Instead of using loops and iterations, Recursion provides sophisticated and straightforward solutions. Using Recursion in programming leads to better strategic thinking and problemsolving techniques. This practice makes the code easy to develop and increase the understandability of the problem.
Formation of Pure Functions
Recursion proves helpful in forming Pure Functions. A pure function refers to a function that returns the value according to the input it receives. Using Recursion, one can simplify problems using pure functions in functional programming, where the user requires solutions to more significant problems.
Time and space complexity
A recursive function makes things easier by calling itself without being dependent on another function. Hence, it makes code short, comprehensible and helps to develop significantly easy algorithms. Moreover, the time complexity of an algorithm is also reduced by it.
Time complexity refers to the total amount of time a program or an algorithm takes to execute. Recursive functions generally produce equal time complexities in comparison to iterative functions. Resultantly, recursive functions complete tasks in a lesser amount of time. However, in some cases, more function calls and returns increase the function’s time complexity significantly.
The space complexity of the recursive function is directly proportional to its depth, i.e., the number of times it has called itself. Furthermore, as the recursive function calls itself repeatedly, the program adds every function on the top of the stack whenever it makes a new call and removes it when the function returns. Therefore, the stack keeps growing, due to which the space complexity of the recursive function is slightly higher or equal to the other functions.
Use of Recursion
Recursion is a very commonly used phenomenon in programming. The programmers use it to find solutions to problems that are breakable into similar smaller problems. For instance, they use it in finding factorial of a provided input. It is also used in numerous algorithms to find the required solution faster such as binary sort, bubble sort, insertion sort, and selection sort.
Additionally, when it comes to solving problems involving graphs and trees, Recursion functions better as it eliminates the risk of using different iterations to visit every node. A recursive function works better at traversing a tree or graph by providing a specific branch or node needed for a solution.
As the recursive functions consume more memory than others, efficient use of call stack in writing a program is essential. The functions where the call stack works smoothly are considered to be efficient while working with Recursion.
How Recursion operates
As mentioned above, Recursion breaks down the problem into smaller problems and then solves them individually to form a complete solution. Recursion does its work by keeping the following steps functional.
Base call
The base call is the part of the function where the function stops after executing it. It is the stop sign for a recursive function to indicate that it has solved the individual problems, and it needs to stop now. If the programmer is not very careful in defining the base case, he may write the infinitely running function, which may crash the program.
Functional working
The functional working refers to a part of the function where it divides the larger problem into smaller subproblems that need to be solved.
Recursive call
Recursive call is an essential part of the function. Here the function calls itself again. However, this time the input is the smaller problem formed in the functional working part.
Example Functions
The following are some basic examples to explain the working of Recursion in coding.
Power function
The power function takes the two inputs: base and power, and calculates base ^ (power). Before the programmer writes the recursive function, he needs to define the function’s logic cases to understand its proper working.
These are the logic cases for the power function:
 If the power is 0 or less than 0, the function returns 1, called the base condition.
 Otherwise, the function calculates the power using x^y.
Mathematical definition
The programmers find out the function’s mathematical definition to make the recursive logic of the function. In the cases above, the user decides only to calculate the positive power of the integers. Additionally, the zeroth power of every integer is 1. Moreover, the simple function of calculating the x power of y integer is to multiple y times x. Every time the number is multiplied by itself, the value of x decreases by 1.
Combining the upper cases gives the following mathematical function f(x, y):
f(x, y) = {1 , x<=0 ; y * f(x1, y) , x>y}
Recursive algorithm of the function
In the C++ programming context, the user needs to:
 Declare a function with a name, such as p().
 Define its input parameters and their types, i.e., p (int power, int base)
 Define the return type of the function, i.e., int.
Converting the mathematical function into C++ function gives:
int p(int power , int base) { if (power <= 0) {//base case return 1; } else { return base * p(power 1 , base); } }
Dry Run
Input: 2, 2 Working :

(2 <= 0) false

Return 2 * p (1, 2)

(1 <=0) false

Return 2* p(0,2)

(0 <=0) true

Return 1

Return 2* 1

Return 2 * 2 * 1
Output: 2*2*1 = 4
Factorial function
The factorial function is the function which multiplies the number with all its predecessors, and is denoted by ‘!’. E.g. the factorial of 4 can be expressed as 4! = 4 X 3 X 2 X 1. In other words, x! = x * (x1) * (x2) * … 2 * 1.
These are the required logic cases to break the factorial problem:
 If the input integer is 0 or 1, the factorial is 1, which is the base case for this function.
 If the input is a positive integer greater than 1, it multiplies the integer with all the numbers below it.
Mathematical Definition
Combining the upper cases gives the following mathematical function f(x):
F(x) = {1 , x=1 or 0 ; x* f(x1) , x>1}
Recursive Algorithm
To write this function in C++, the user needs to:
 Declare a function with a name, such as factorial ().
 Define its input parameters and their types, i.e., factorial (int number)
 Define the return type of the function, i.e., int.
Converting the mathematical function into C++ gives:
int factorial( int number) { if (number == 1) {//base case return 1; } else { return number * factorial(number  1); } }
Dry Run
Input: 3 Working :

(3 ==1) false

Return 3 * factorial(2)

(2 ==1) false

Return 2* factorial (1)

(1==1) true

Return 1

Return 2 *1

Return 3 * 2 *1
Output: 3*2*1 = 6
Lastly, it is essential to consider that Recursion may work best for one problem but may not be the best solution for the other. Therefore, programmers need to choose carefully, depending on the problem they want to solve. Although the recursive approach provides an elegant and shorter solution in terms of coding, it sometimes can be impractical.