Contents

- 1 When is the recursion guaranteed to be finite?
- 2 Is it appropriate to use recursion in every problem?
- 3 What are the two parts of a recursive implementation?
- 4 How to visualize the execution of a recursive function?
- 5 Which is an example of how recursion works?
- 6 How to find the time complexity of recursion?
- 7 Which is more difficult to find iteration or recursion?

## When is the recursion guaranteed to be finite?

If every recursive step shrinks the problem, and the base case lies at the bottom, then the recursion is guaranteed to be finite. A recursive implementation may have more than one base case, or more than one recursive step. For example, the Fibonacci function has two base cases, n=0 and n=1.

## Is it appropriate to use recursion in every problem?

Recursion is not appropriate for every problem, but it’s an important tool in your software development toolbox, and one that many people scratch their heads over. We want you to be comfortable and competent with recursion, because you will encounter it over and over. (That’s a joke, but it’s also true.)

## What are the two parts of a recursive implementation?

A recursive implementation always has two parts: base case, which is the simplest, smallest instance of the problem, that can’t be decomposed any further. Base cases often correspond to emptiness – the empty string, the empty list, the empty set, the empty tree, zero, etc.

## How to visualize the execution of a recursive function?

The recursive step is n > 0, where we compute the result with the help of a recursive call to obtain (n-1)!, then complete the computation by multiplying by n. To visualize the execution of a recursive function, it is helpful to diagram the call stack of currently-executing functions as the computation proceeds.

## Which is an example of how recursion works?

Let us take the example how recursion works by taking a simple function. When printFun (3) is called from main (), memory is allocated to printFun (3) and a local variable test is initialized to 3 and statement 1 to 4 are pushed on the stack as shown in below diagram. It first prints ‘3’.

## How to find the time complexity of recursion?

Recursion: Time complexity of recursion can be found by finding the value of the nth recursive call in terms of the previous calls. Thus, finding the destination case in terms of the base case, and solving in terms of the base case gives us an idea of the time complexity of recursive equations.

## Which is more difficult to find iteration or recursion?

Time Complexity: Finding the Time complexity of Recursion is more difficult than that of Iteration. Recursion: Time complexity of recursion can be found by finding the value of the nth recursive call in terms of the previous calls.