Concept

Pivot — where it appears

The element a partition compares everything against, whose choice decides whether quicksort is linearithmic or quadratic on a given input. Choosing it at random converts a bad input into bad luck, which is a guarantee on every input rather than on most of them.

Named by 17 essays across 8 fields — each of them below, with the objects they name alongside it.

mean 494599th 60304,2825,4136,543comparisonsruns600 independent random inputs, n = 512worst run 1.32× the mean

The words "on average" are not a number

Quicksort is Θ(n log n) on average. Six hundred runs at n = 512 give a distribution with a mean of 4,945 comparisons, a median of 4,908, and a worst case 32% above the mean. The average is a summary of that picture, it is the least interesting thing in it, and it is almost always the only thing reported.

wrong · Distribution
Timsort95,770shipsIntrosort130,863shipspdqsort114,408shipsDual-pivot116,836shipsMerge sort96,145textbookHeapsort187,796textbookQuicksort, median-3119,098textbookalgorithmcomparisonsrandom, n = 8,192comparisons, counted exactly

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.

practice · Practice
comparisons ÷ n log nMerge sort0.855Merge sort with a cutoff0.992Quicksort, random pivot1.018Quicksort, first-element1.082Quicksort, median of three1.117Shellsort1.246Heapsort1.649all of these fit n log n1.9× between best and worst

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.

bounds · Bound
10010³1010010³nstack framesa stack of 512 framespivot: first-elementpivot: median of threepivot: random pivotMerge sortalready sorted input, n from 64 to 4,096one frame charged as one slot

The stack nobody counts

Merge sort makes 8,192 calls to sort 4,096 elements and holds fourteen of them at once. Depth-first search on a grid holds twelve vertices, or sixty-six, or a hundred and forty-four, depending on which of three equally standard implementations is running. The stack is a resource, it is the one that fails hard rather than slowly, and nothing that watches the data can see it.

space · Space
first-element pivot130,816 on sortedmedian of three5088 meanrandom pivot4937 meanblue bar: range over 400 random inputs · marker: the already-sorted inputn = 512a bad case that cannot be chosen is a different kind of bad case

What randomising the pivot buys

Quicksort taking the first element as its pivot costs 130,816 comparisons on an already sorted array of 512 — 27 times its cost on random data, and exactly the quadratic behaviour the algorithm exists to avoid. Randomising the pivot costs 5,490 on the same input. Randomisation does not make the bad case impossible; it makes it unchoosable.

wrong · Distribution
comparisonsswapsInsertion sort63,071 / 0Selection sort130,816 / 504Bubble sort129,688 / 62,563Merge sort3,964 / 0Heapsort7,653 / 4,170Quicksort5,049 / 2,380n = 512, random inputcounted in the same run

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.

counting · Count
10⁵10⁶10⁷11010010³10⁴comparisonspeak auxiliary slotsInsertion sortSelection sortBubble sortMerge sortHeapsortQuicksortQuicksortQuicksortShellsortMerge sort with a cutoffn = 8,192, random input5 on the frontier, 5 dominated

The frontier between time and space

The question of which sorting algorithm to use has an honest answer, and it is a shape rather than a name. Comparisons on one axis, peak auxiliary space on the other, and five of the ten algorithms here are on the Pareto frontier while five are dominated — beaten on both counts at once, so that no weighting of the two costs makes them the right choice. Heapsort is one of the five that lose.

space · Space
sorted insertion — height 62shuffled insertion — height 10truncated at depth 1663 keys, identical set, different arrival order62 deep against 10

The tree that is a list

A binary search tree gives logarithmic lookup. Build one from 128 keys in sorted order and it has height 127 — every node has one child, and a lookup is a linear scan. The failure is not gradual and it happens on the input people try first, which makes "O(log n) lookup" a claim about the insertion order rather than about the structure.

structures · Structure
quicksort on sorted input — comparisonsfirst-element pivot2,096,128random pivot25,318a search tree built from sorted keys — heightbinary search tree2,047treap26a hash table on keys chosen to collide — worst bucketthe low bits of the key2,048multiply–shift, a at random10n = 2,048, bars on a logarithmic scaledeterministic above, randomised below

Expected is not average

Quicksort on 2,048 sorted keys costs 2,096,128 comparisons with a first-element pivot and 25,318 with a random one. A binary search tree on the same keys is 2,047 deep; a treap is 26. A hash table on keys computed against its hash puts all 2,048 in one bucket; one drawn from a family puts at most 10 there. Three problems, one distinction.

bounds · Distribution
peak slots held at once, logarithmic18645124096Insertion sort11Selection sort11Bubble sort11Heapsort11Shellsort11Quicksort, median of three14log nQuicksort, random pivot32log nQuicksort, first-element4,097nMerge sort with a cutoff4,106nMerge sort4,110nn = 4,096, already sorted inputone slot = one array element or one stack frame

In place is a claim, and it is usually wrong about quicksort

Heapsort holds one slot at its peak. Quicksort holds twenty-two at n = 4,096 on random input and 4,097 on a sorted one. Merge sort holds 4,110. All three are described with the same two words, one of the three descriptions is false, and the false one is the algorithm the phrase is most often attached to.

wrong · Space
algorithmspread of count ⁄ f(n) — 1.0 is exactTimsortPython, Java objects, Rust, Android1.176nIntrosortC++ std::sort1.104n log nPattern-defeating quicksortRust unstable sort, Boost, libstdc++ 141.155nDual-pivot quicksortJava Arrays.sort, primitives1.624no class grantedtolerance 1.6fitted n = 256–16,384comparisons, counted exactly

The pattern that defeats the pattern

Quicksort's bad cases are patterns — sorted input, organ-pipe input, an adversary's construction. Introsort's answer is to notice the damage and switch algorithms. pdqsort's answer is to notice the pattern and break it, deterministically, with four swaps. On input with eight distinct values that turns a quadratic disaster into a linear sort, and the whole difference is one extra partition scheme.

practice · Practice
the floor that applieslog₂(n!)Merge sort2.3×1,682Shellsort2.3×1,714Merge sort + cutoff2.6×1,938Heapsort4.2×3,101Quicksort, first6.6×4,887Quicksort, random7.2×5,291Quicksort, median-37.8×5,728Insertion sort18.5×13,644Bubble sort43.1×31,820Selection sort44.2×32,6408 distinct values, n = 256, seededthe two floors are 2.28× apart

The floor when the values repeat

log₂(n!) counts orderings of distinguishable things. Two hundred and fifty-six values drawn from eight distinct ones have 1,684 bits of permutation entropy and 739 bits of distinguishability, so the real floor is less than half the one every table quotes — and merge sort, which sits exactly on the quoted floor, is 2.3 times above the one that applies.

floors · Floor
randomised pivot164 random bits2.96 ±23%median of mediansno random bits7.94 ±2%0.04.38.6comparisons per element — bar is the range over seeds, tick is the mean30 seeds, n = 4,001, median2.68× the mean, 14× the spread

What derandomising costs

Randomised selection finds the median of twenty thousand elements in 3.21 comparisons per element and median-of-medians takes 8.15 — two and a half times as many for the same answer, both linear. The number that decides between them is not either of those. It is that the first varies by 28% from seed to seed and the second by 1.6%.

bounds · Distribution
10³10⁴10⁴array length ntotal over 2,000 searchesbranchy, comparisonsbranchless, comparisonsbranchy, mispredictsbranchless, mispredicts2-bit counters, no historysolid: comparisons · dashed: mispredicts

A search with no branch to miss

A binary search does about log₂ n comparisons and every one of them is a coin flip, so it mispredicts once per level. Writing it so the comparison feeds an index instead of a jump costs two thousand extra comparisons over two thousand searches and takes the mispredictions from 17,993 to 2,001 — flat in n, at every size. Under the counters this site had a phase ago, that is a strictly worse algorithm.

machine · Machine
average 8.001,0242,048bucket, 0 to 255keys in the bucketmultiply–shift · keys built for this hashworst bucket 2,048 against 8.0

The adversary who knows the seed

Every randomised figure on this site is drawn from a stated seed, so that the numbers in the captions are the numbers on the reader's screen. That is also the exact condition under which none of the guarantees those figures demonstrate applies. A published seed is a published function.

wrong · Distribution
10³10³10⁴10⁵10⁶10⁷ncomparisonsadversary, no depth limitadversary, as it shipsrandom inputn²/2McIlroy's adversary, answering as it goescomparisons, counted exactly

The depth limit that almost never fires

Introsort counts how deep its recursion has gone and calls heapsort if it passes twice the logarithm. On every input measured, the mechanism handles under a tenth of a per cent of the elements. Then an adversary that answers the comparisons rather than choosing the array drives it to exactly n²/2 with the limit removed, and to one heapsort call with it — a factor of forty-two at n = 8,192, and growing.

bounds · Bound
Dual-pivot116,836shipsIntrosort130,863shipspdqsort114,408shipsTimsort95,770shipsalgorithmcomparisonsrandom, n = 8,192comparisons, counted exactly

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.

counting · Count

Named alongside it

The objects these essays reach for when they reach for this one.

QuicksortGuaranteePartitionComparison countDistributionSwapsWorst caseCutoffIntrosortpdqsortRandomised algorithmRanking

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