Folding and reducing data sets

While the map() operator takes a list of a given size and returns another list of the same size and of the modified type, the fold() and reduce() operations applied to the data set return a single element, composed of the consecutive elements of the data set. This may sound like a simple scenario for using a plain, imperative-style loop and local accumulator variable that holds a current state and is updated at each iteration. We can consider the simple task of summing up integer values. Let's consider that we want to compute a sum of consecutive integers from 0 to 10. We could achieve it using a simple for loop:

var sum = 0
(1..10).forEach {
    sum += it
}

However, there is an alternative, functional way of performing such computations, using the fold() function:

val sum = (1..3).toList().fold(0) { acc, i -> acc + i }

The second approach is desirable whenever we implement a chain of functional data-processing operations. Compared to the for loop, the fold...