The thread: The threshold is the algorithm
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.
What the libraries doWhen galloping pays
Timsort's merge does not always take elements one at a time. When one run has won seven times in a row it switches to searching for how many to take at once, and switches back when that stops paying. The mode saves 22,104 comparisons on nearly sorted input, 33,270 on input with few distinct values, and costs exactly six on random input — which is the whole design in three numbers.
What the libraries doThe 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.
Two parametersThe precondition on a function the caller writes
Dijkstra expands 1,582 cells to find a path of 98 across a fifty-square grid. The same loop, with the straight-line distance to the goal added to each key, expands 405 and finds the same 98. The estimate has to be a function the caller supplies, and the guarantee holds only while that function never overestimates — a condition on somebody else's code, not on the graph.
What the libraries doThe 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.
When the algorithm flips a coinAn insertion that can fail
Every randomised structure in this field buys an expected cost and accepts a tail. Cuckoo hashing buys a worst case — a lookup examines exactly two slots, for any keys, always — and pays for it in the construction, which can fail outright. On a table of four thousand slots the construction never fails below 0.45 keys per slot and fails nineteen times in twenty above 0.55.
What a bound isThe 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.
What the libraries doThe dictionary that builds itself
LZSS contains no probability, no frequency table and no entropy calculation. Its entire model is a window of recent text and its only move is to say "the next nine symbols are the ones that appeared 1,200 positions ago". On a stream whose zeroth-order floor is 3.89 bits per symbol it spends 2.11, and widening its window past 4,096 makes it worse rather than better.
StructuresThe probe nobody waits for
Robin Hood hashing makes an inserting key steal a slot from a key that has probed less far. The mean number of probes afterwards is 4.817, and before it was 4.817 — identical, and it cannot be otherwise, because the total displacement is fixed by the hash. What changes is the worst case, from 114 slots from home to 19, and a table reported by its average lookup cost shows no difference at all.
When it does not fitOne dial between two structures
A B-tree writes 226 elements of block for every key stored and a log-structured store writes two. They are presented as rival designs. They are one design at two settings of an exponent that nothing in either description mentions, and every setting between them is available.
StructuresA bucket that becomes a tree
Java's HashMap converts a chained bucket into a red-black tree once it holds eight entries. The comment in the source computes the probability of that happening under a decent hash at about six in a hundred million, so the mechanism is written never to run. Under a hash that fails, the worst lookup falls from 192 comparisons to 8 — and the whole value of the tree is in a case its author does not control.
The data that is not a numberOne pass for every pattern at once
Sixty-four patterns, one text, twenty thousand characters read. Running this site's KMP once per pattern reads 1,595,445 — and an implementation missing one kind of link finds fewer occurrences, reads exactly as much, and looks better on every counter.
When it does not fitThe estimate a plan rests on
A planner chooses between an index and a scan on how many rows it thinks will match, and the number it has is wrong by a factor. Guess sixty-four times too many on a narrow query and the scan it picks costs 13.5 times the index. Guess sixty-four times too few on a wide one and the index costs at most 4.01 times the scan — a ceiling that can be named before any query runs.
When the algorithm flips a coinMore hashes or wider buckets
A cuckoo table with two hash functions and one slot per bucket cannot be built past about half full. Give it a third hash function and it builds to 0.92. Keep two hashes and give each bucket two slots and it builds to 0.89; four slots, past 0.95. Every shape keeps the worst-case lookup the plain table was built for, and every shape pays for its threshold in a different place.
What the libraries doThe rule that pays on a long enough text
With two patterns, the cheap tables cost 106 steps and the scan reads 13,084 characters; the exact tables cost 594 and the scan reads 12,306. Below thirty-two thousand characters the cheap tables win the total, above it the extra skipping pays for them, and with thirty-two patterns there is no crossing at all.
What the libraries doThe number that would choose a cap
A depth histogram is one linear pass — 3.16 operations a character over thirty-two thousand of them — and it says the whole text sits at a mean depth of 3.98 with a worst of ten. Nobody prints it, and every choice of cap in this collection was made without it.
The data that is not a numberThe search that starts in the middle
The same pattern, the same six occurrences, the same index — and 830 interval extensions, or 303, according to which end the search begins at. A pattern cut into three pieces has an error-free one, and only a search with two ends can start there.
What the libraries doA looser budget wastes a larger share
More errors permitted means more work, and the fraction of that work which was never going to help rises with it — from thirty-one per cent at no errors to seventy-five at two. The saving is worth most where the search is most expensive.
What the libraries doThe saving that is a loss
An operation that is seventy-eight times cheaper on a branching search costs twice as much on an exact one. It reports every symbol present in order to hand back the one that was asked for, and a search that knows its character needs none of the rest.
What the libraries doWhere the table starts paying
Five thousand and sixty-five operations before the first character, then one per character. Against nothing before the first character and thirty-nine per character. They cross at two hundred and fifty-six characters, and that crossing is what an engine's compile decision actually is.
What is taught wronglyA cache below the reachable set
A lazy machine with a cache of two hundred and fifty-six states costs fifty-one operations a character and a plain non-deterministic simulation costs fifty-three. At five hundred and twelve it costs eleven. The line is flat across two orders of magnitude and then falls off a cliff.