Recursion is a concept and technique in mathematics and computer science where a function calls itself directly or indirectly. To understand recursion, it's important to start from basic principles:

**Definition of a Function**: In mathematics and computer science, a function is a process or a relation that associates each element of a set (the domain) with exactly one element of another set (the codomain). For example, a function`f(x)`

might assign each number`x`

to its square`x^2`

.**Self-Reference**: Recursion occurs when a function, in the course of its execution, calls itself. This is known as self-reference. In the broader sense, self-reference means referring back to oneself or the same thing.**Base Case**: To prevent infinite looping, a recursive function must have a base case. This is a condition under which the function does not make a recursive call. In other words, it's the scenario where the function can provide an answer directly without needing to call itself.**Recursive Case**: This is the part of the function where recursion actually occurs. Here, the function splits the problem into smaller parts, calls itself with these smaller parts, and then possibly combines the results of these calls to produce the answer.**Simplification Towards Base Case**: Each recursive call must simplify the problem, moving it closer to a base case. This ensures that the recursion will eventually terminate when it reaches a base case.**Stack Memory in Computing**: In computer science, recursion is closely linked with the concept of stack memory. Each time a function calls itself, a new frame is placed on the stack with its own set of variables. Once the function hits its base case and returns, these frames are popped off the stack.

The factorial of a number `n`

, denoted as `n!`

, is the product of all positive integers less than or equal to `n`

. It's a classic example to illustrate recursion.

The factorial function can be defined recursively:

**Base Case**:`0! = 1`

. This is straightforward and needs no further breakdown.**Recursive Case**:`n! = n * (n-1)!`

. This is the recursive step, where the function calls itself with`n-1`

.

In pseudocode, a recursive factorial function looks like this:

```
function factorial(n)
if n is 0
return 1
else
return n * factorial(n - 1)
```

When you call `factorial(5)`

, the function calls itself repeatedly until it reaches the base case:

`factorial(5)`

`5 * factorial(4)`

`5 * (4 * factorial(3))`

`5 * (4 * (3 * factorial(2)))`

`5 * (4 * (3 * (2 * factorial(1))))`

`5 * (4 * (3 * (2 * (1 * factorial(0)))))`

`5 * (4 * (3 * (2 * (1 * 1))))`

(as`factorial(0)`

is 1)- And then it resolves back up the stack to give
`120`

.

The Fibonacci sequence is another classic example of recursion. Each term in the sequence is the sum of the two preceding ones. Mathematically, it's defined as:

**Base Cases**:`Fib(0) = 0`

,`Fib(1) = 1`

**Recursive Case**:`Fib(n) = Fib(n-1) + Fib(n-2)`

Understanding recursion is crucial because it provides a powerful tool for solving problems that can be broken down into smaller, similar problems. However, it's important to use recursion judiciously, as improper use can lead to inefficiencies or stack overflow errors in computing.