The iterative nature of a solution should always come out in the design stage of development, not during implementation. The algorithms described in the design should aim at minimizing the number of iterations. For example, the number of iterations performed by a selection sort on a list of N elements is roughly N², while the number of iterations performed by a heap sort is roughly N * log(N). Note that this has nothing to do with the programming language. In the design phase, we have not yet decided on a programming language. Regardless of what language we choose later, in the implementation phase, we will prefer the heap sort algorithm over the selection sort.

Note that if N is very small, it doesn't matter much whether we use a selection sort or a heap sort. However, we should never make such assumptions about the data. A function as generic as a sorting algorithm is not just useful to this program. It should be written in a way that it can be used in any program, so that we don't waste time rewriting it later. So, we decide during the design phase to use the fastest sort algorithm, and we decide during the implementation phase to use a compiled language, since sorting is computationally expensive. Using an interpreted language could make the sort run for hours instead of minutes.

Regardless of the complexity of a problem, implementation should always be a fairly simple process of translating the design. The design of the sorting algorithm tells us exactly what the code must do, so writing the code in any language should be an uneventful process.