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Scala Recursion with Examples

Recursion is a fundamental concept in functional programming, and Scala, being a hybrid functional programming language, supports recursion extensively. In this article, we’ll explore recursion in Scala, including the difference between normal and tail recursion, with practical examples to help you understand its application.

What Is Recursion?

Recursion occurs when a function calls itself within its definition to solve a problem by breaking it down into smaller subproblems. This approach is particularly effective for tasks that can be divided into similar, smaller tasks, such as calculating factorials, Fibonacci sequences, or traversing data structures like trees.

Scala’s recursion support enables developers to write elegant, functional solutions for such problems.

Normal Recursion in Scala

Normal recursion involves a function repeatedly calling itself until a base condition is met. Below is an example of a recursive function to calculate the factorial of a number:

def factorial(n: Int): Int =
  if (n == 0) 1 else n * factorial(n - 1)

println(factorial(5)) // Output: 120

How It Works

1. The function keeps calling itself with a smaller value of n until n == 0.
2. Once the base condition (n == 0) is met, the recursion stops, and the function returns 1.
3. The intermediate results are then multiplied as the function "unwinds."

Tail Recursion in Scala

Tail recursion is a special form of recursion where the recursive call is the last operation in the function. This is more memory-efficient because Scala can optimize tail-recursive functions to avoid stack overflow errors, even for deep recursions.

You can use the @tailrec annotation to ensure a function is tail-recursive:

import scala.annotation.tailrec

@tailrec
def factorialTailRec(n: Int, accumulator: Int = 1): Int = {
  if (n == 0) accumulator
  else factorialTailRec(n - 1, accumulator * n)
}

println(factorialTailRec(5)) // Output: 120

How It Works

1. An accumulator parameter is introduced to carry the result of the computation.
2. The function computes the result incrementally, passing it along as the accumulator.
3. Since the recursive call is the last operation, the function is optimized by the Scala compiler to reuse the current stack frame.

Key Differences Between Normal and Tail Recursion

When to Use Recursion in Scala

• Recursive solutions are ideal for problems involving repetitive subproblem solving, like:

  • Factorial calculations
  • Fibonacci sequence generation
  • Tree traversal (e.g., binary trees)
  • Divide-and-conquer algorithms (e.g., quicksort, mergesort)

• Prefer tail recursion for scenarios with deep recursion to avoid stack overflow.

Conclusion

Scala’s support for recursion, especially tail recursion, allows developers to write clean and efficient code. Understanding the differences between normal and tail recursion helps you choose the right approach for your use case. By incorporating the @tailrec annotation, you can ensure your functions are optimized and safe from stack overflow errors.

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