Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Smoothsort

In computer science, smoothsort is a comparison-based sorting algorithm. A variant of heapsort, it was invented and published by Edsger Dijkstra in 1981. Like heapsort, smoothsort is an in-place algorithm with an upper bound of O(n log n) operations (see big O notation). Like heapsort, smoothsort is not a stable sort. The advantage of smoothsort is that…

Applications, Standards & Science

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Smoothsort. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Overview

Computer scienceComparison-basedSorting algorithmHeapsortEdsger Dijkstra
17 related topics

Applications

MuslQsort
2 related topics

Poplar sort

PoldersAmortizedBinomial heap
3 related topics

Analysis

Bit vectorTransdichotomous machine model
2 related topics

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Average performance
O(n log n)
Best-case performance
O(n)
Class
Sorting algorithm
Data structure
Array
Optimal
When the data is already sorted
Worst-case performance
O(n log n)

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Operations

Analysis

Poplar sort

Applications

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Smoothsort

Nodes31
Edges30
Triples48
Avg. degree1.94
Density0.064516
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Smoothsort

Top relations

related to External links · 16
Smoothsort → Algorithm Implementation/Sorting/SmoothsortDescription, April, Aug-1981Detailed, Commented, Computer Science, EWD796a, Japanese, Kohei, Mathematical Foundations, Nakatani, Nested Heap Structure, On, Poplar, Smoothsortwikibooks, Their Applications, Yoshinobu
related to overview · 8
Smoothsort → Also, Each, Every, Heapsort, Its, Like, This, When
related to Analysis · 6
Smoothsort → However, Leonardo, Moreover, Since, The, Using
related to Poplar sort · 4
Smoothsort → Dutch, Instead, Named, The
related to Sifting down · 4
Smoothsort → Dijkstra, If, So, The
is a · 2
Smoothsort → comparison-based sorting algorithm, in-place algorithm with an upper bound of O
Average performance · 1
Smoothsort → O(n log n)
Best-case performance · 1
Smoothsort → O(n)
Class · 1
Smoothsort → Sorting algorithm
Data structure · 1
Smoothsort → Array

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

heap sorted array tree heapsort root element stretches log roots algorithm two children stepson time binary size node dijkstra sorting

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
SmoothsortAverage performanceO(n log n)1.00infobox
SmoothsortBest-case performanceO(n)1.00infobox
SmoothsortClassSorting algorithm1.00infobox
SmoothsortData structureArray1.00infobox
SmoothsortOptimalWhen the data is already sorted1.00infobox
SmoothsortWorst-case performanceO(n log n)1.00infobox
SmoothsortWorst-case space complexityO(n) total, O(1) auxiliary1.00infobox
Smoothsortis acomparison-based sorting algorithm0.90text
Smoothsortis ain-place algorithm with an upper bound of O0.90text
Smoothsorthas applicationThe0.60section
Smoothsortrelated to AnalysisHowever0.60section
Smoothsortrelated to AnalysisUsing0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.