Have you also looked at its memory consumption? Note that quicksort itself is worse than linear, with a quite bad worse case runtime. This multiplies with the worse than linear runtime behaviour of certain steps of template compilation and instantiation (sometimes those are exponentional). You should maybe graph your compiletime for various datasets to observe … Read more
Quicksort (recursive) function quicksort(array) { if (array.length <= 1) { return array; } var pivot = array[0]; var left = []; var right = []; for (var i = 1; i < array.length; i++) { array[i] < pivot ? left.push(array[i]) : right.push(array[i]); } return quicksort(left).concat(pivot, quicksort(right)); }; var unsorted = [23, 45, 16, 37, 3, … Read more
Quicksort (recursive) function quicksort(array) { if (array.length <= 1) { return array; } var pivot = array[0]; var left = []; var right = []; for (var i = 1; i < array.length; i++) { array[i] < pivot ? left.push(array[i]) : right.push(array[i]); } return quicksort(left).concat(pivot, quicksort(right)); }; var unsorted = [23, 45, 16, 37, 3, … Read more
I think that the issue here is that your partitioning step does not necessarily shrink the input array. For example, let’s trace what happens if you try sorting [1, 2]. In this case, your pivot element will be the element 2. Since 1 > 2 is false, 1 is added to the list l. Since … Read more
Big-O Notation describes the limiting behavior when n is large, also known as asymptotic behavior. This is an approximation. (See http://en.wikipedia.org/wiki/Big_O_notation) Insertion sort is faster for small n because Quick Sort has extra overhead from the recursive function calls. Insertion sort is also more stable than Quick sort and requires less memory. This question describes … Read more
Quicksort’s performance is dependent on your pivot selection algorithm. The most naive pivot selection algorithm is to just choose the first element as your pivot. It’s easy to see that this results in worst case behavior if your data is already sorted (the first element will always be the min). There are two common algorithms … Read more
Consider what happens during the partition for the following array of pairs, where the comparator uses the integer (only). The string is just there so that we have two elements that compare as if equal, but actually are distinguishable. (4, “first”), (2, “”), (3, “”), (4, “second”), (1, “”) By definition a sort is stable … Read more
Both quicksort and mergesort can work just fine if you can’t fit all data into memory at once. You can implement quicksort by choosing a pivot, then streaming elements in from disk into memory and writing elements into one of two different files based on how that element compares to the pivot. If you use … Read more
Intro to Algorithms from MIT Press qualifies QuickSort as in-place – it sorts the elements within the array with at most a constant amount of them outside the array at any given time. At the end of the day, people will always have differing opinions (is Top-Down Memoization considered Dynamic Programming? Not to some “classical” … Read more
The median of three has you look at the first, middle and last elements of the array, and choose the median of those three elements as the pivot. To get the “full effect” of the median of three, it’s also important to sort those three items, not just use the median as the pivot — … Read more