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    <p>One of the main benefits of recursion is that it lets you create solutions without mutation. for following example, you have to calculate the sum of all the elements of a List. </p> <p>One of the many ways to solve this problem is as below. The imperative solution to this problem uses for loop as shown:</p> <pre><code> scala&gt; var total = 0 scala&gt; for(f &lt;- List(1,2,3)) { total += f } </code></pre> <p>And recursion solution would look like following:</p> <pre><code> def total(xs: List[Int]): Int = xs match { case Nil =&gt; 0 case x :: ys =&gt; x + total(ys) } </code></pre> <p>The difference is that a recursive solution doesn’t use any mutable temporary variables by letting you break the problem into smaller pieces. Because Functional programming is all about writing side effect free programs it's always encourage to use recursion vs loops (that use mutating variables). </p> <p>Head recursion is a traditional way of doing recursion, where you perform the recursive call first and then take the return value from the recursive function and calculate the result. </p> <p>Generally when you call a function an entry is added to the call stack of a currently running thread. The downside is that the call stack has a defined size so quickly you may get StackOverflowError exception. This is why Java prefers to iterate rather than recurse. Because Scala runs on the JVM, Scala also suffers from this problem. But starting with Scala 2.8.1, Scala gets away this limitation by doing tail call optimization. you can do tail recursion in Scala. </p> <p>To recap recursion is preferred way in functional programming to avoid using mutation and secondly tail recursion is supported in Scala so you don't get into StackOverFlow exceptions which you get in Java.</p> <p>Hope this helps.</p>
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    1. POIs recursion in scala very necessary?
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    1. USVikas Pandya
    1. USVikas Pandya
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    1. COActually, an optimal Scala solution to that would look like List(1, 2, 3).sum, or slightly more generally List(1, 2, 3).fold(0)(_+_) . Recursion is best used when the built-in higher-order combinators don't quite fit.
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      1. USDave Griffith
 

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