Recursion in Scala - GeeksforGeeks

29 Mar, 2019
Recursion is a method which breaks the problem into smaller sub problems and calls itself for each of the problems. That is, it simply means function calling itself. We can use recursion instead of loops. Recursion avoids mutable state associated with loops. Recursion is quite common in functional programming and provides a natural way to describe many Algorithms. Recursion is considered as to be important in functional programming. Scala supports Recursion very well.
Let us understand using the simple factorial example.Example :
// Scala program of factorial using recursion  // Creating objectobject GFG{    // Function define    def fact(n:Int): Int=    {        if(n == 1) 1        else n * fact(n - 1)    }          // Main method    def main(args:Array[String])    {        println(fact(3))    }}
Output:
6
The above code demonstrated in a recursive approach to a factorial function, where the condition n == 1 results in a break from the recursion.
Let us understand more clearly by an example of gcd.Example :
// Scala program of GCD using recursion  // Creating objectobject GFG{    // Function defined    def gcd(x:Int, y:Int): Int=    {        if (y == 0) x        else gcd(y, x % y)    }          // Main method    def main(args:Array[String])    {        println(gcd(12, 18))    }}
Output:
6
Problem with recursion is that deep recursion can blow up the stack if we are not careful.Let’s understand this by using an example:Example Code:
// Scala program of sum all numbers// using recursion   // Creating objectobject GFG{    // Function defined    def sum(num: Int): Int=    {        if (num == 1)            1        else            sum(num - 1) + num    }          // Main method    def main(args:Array[String])    {        println(sum(55))    }}
Output:
1540
The method sum will do the summation of all the numbers. We reduce the num everytime and add it to the result. Here, whenever we call sum, it will leave input value num on the stack and using up memory every time. when we try passing a large input like sum(555555) than the output will be java.lang.StackOverflowError. This output means that the stack has been blown up.
The above example does not use tail recursion and is therefore not an optimal approach, especially if the starting value n is very large.
The tail recursive functions considered better than non tail recursive functions as tail-recursion can be optimized by compiler. A recursive function is said to be tail recursive if the recursive call is the last thing done by the function. There is no need to keep record of the previous state.Let us understand it by a example:
Example :
// Scala program of factorial using tail recursionimport scala.annotation.tailrec  // Creating objectobject GFG{    // Function defined    def factorial(n: Int): Int =    {        // Using tail recursion        @tailrec def factorialAcc(acc: Int, n: Int): Int =        {            if (n <= 1)                acc            else                 factorialAcc(n * acc, n - 1)        }        factorialAcc(1, n)    }          // Main method    def main(args:Array[String])    {        println(factorial(5))    }}
Output:
120
Here in the above code, we can use the @tailrec annotation to confirm that our algorithm is tail recursive.
If we use this annotation and our algorithm isn’t tail recursive, the compiler will complain. For instance, if we attempt to use this annotation on the above example of the factorial method, we will get the following compile-time error.
Example :
// Scala program of factorial with tail recursionimport scala.annotation.tailrec  // Creating objectobject GFG{    // Function defined    @tailrec def factorial(n: Int): Int =    {        if (n == 1)            1        else             n * factorial(n - 1)    }          // Main method    def main(args:Array[String])    {        println(factorial(5))    }}
Output:
Could not optimize @tailrec annotated method factorial: it contains a recursive call not in tail position
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