Rotation — where it appears
Named by 3 essays across 2 fields — each of them below, with the objects they name alongside it.
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.
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.
The priority nobody supplied
Insert 4,096 sorted keys into a binary search tree and it reaches height 4,095, costing 8,386,560 comparisons to build. Give every key a second, random key and keep the tree heap-ordered on that instead, and the same insertion reaches height 26 for 32,750 comparisons. Nothing detected the imbalance, and nothing rebalanced.
Named alongside it
The objects these essays reach for when they reach for this one.
GuaranteeBinary searchBinary search treeInsertion orderPivotQuicksortWorst caseAmortised analysisAuxiliary spaceBalanceCacheComparison count