It has to do with how you decompose problems. In the example I gave, I was trying to point out that arithmetic average, geometric average, and normalization are related problems. Consider applying this technique to something more complicated than averages: pathfinding. You could create a dozen different efficient functions, each with different considerations, but the core of the algorithm will always be the same. You can write pathfind_land(src, dest), pathfind_sea(src, dest), pathfind_air(src,dest), pathfind_sea_and_land(src,dest) etc. but it’s obviously better to write it as pathfind(src,dest, is_traversable) and select the most efficient implementation inside the function. It also allows you to use a not-optimized implementation automatically if you haven’t made an efficient implementation.