Cutoff — where it appears
Named by 7 essays across 4 fields — each of them below, with the objects they name alongside it.
The sort the library ships
Every sorting algorithm measured on this site so far has one thing in common — none of them is what runs when a program calls sort. Python, Java, Rust and Android run Timsort; C++ runs introsort; Java's primitive sort is dual-pivot quicksort. Not one of the four was in this collection, and the reason it matters is that they are not algorithms in the sense the other essays use the word.
The constant the notation drops
Six algorithms on this site are Θ(n log n) and their comparison counts differ by a factor of two. The class is what they have in common; the constant is what distinguishes them. It is measurable to three digits, it is the number that actually decides between them, and it is precisely the number the classification is designed to discard.
A limit is not a prediction
Measured from n = 64 to n = 4,096, this site's hybrid merge sort fits a linear class better than n log n. Measured out to n = 65,536, the ranking reverses. Nothing changed but the range — and this is not a flaw in the method, it is the method finding the exact place where measurement stops being able to help.
One run, four counts, four answers
The question “how many operations” has no answer until the operation is named. Selection sort makes more comparisons than any other algorithm here and fewer writes than almost all of them; bubble sort matches its comparisons and does 124 times the swapping. The ranking depends entirely on which count is chosen, and the choice needs justifying.
Where insertion sort actually wins
Every production sorting routine falls back to insertion sort on small subarrays, and the usual explanation is that below some threshold it does fewer comparisons. Measured, it does not — not at sixteen elements, not at eight, not at four. The crossover is real and it is entirely in memory traffic, which is a distinction the usual telling loses.
The threshold somebody chose
A minrun of 32. An insertion cutoff of 16. A gallop threshold of 7. A depth limit of twice the logarithm. Four numbers, in four real source files, none of which appears in any complexity analysis — and each of which decides more about what these algorithms do than the analysis does. Swept, they turn out not to be optima, and finding out what they are instead is the point.
Two pivots and what they cost
Java changed its primitive sort in 2011 on the strength of an analysis showing dual-pivot quicksort does fewer comparisons than the classical one. It does. It also does nearly twice the swaps, and the analysis that decided the matter counted neither — it counted a weighted combination that had to be chosen before any conclusion could be drawn.
Named alongside it
The objects these essays reach for when they reach for this one.
Comparison countQuicksortPivotRankingThresholdIntrosortPartitionSwapsTimsortCacheComplexity classConstant factor