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Topic orientation
Persistent data structure at a glance
The strongest research directions include Examples of persistent data structures and Usage in programming languages. Use the connected concepts below as starting points, not as a keyword checklist.
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Explore the main themes, entities and connections around Persistent data structure. 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.
Examples of persistent data structures
30 related topics
Usage in programming languages
Pure functional languageReferential transparencyJava collections frameworkValue semanticsParallel computing
17 related topics
Techniques for preserving previous versions
8 related topics
Garbage collection
4 related topics
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Topics to explore
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.Browse the full topic structure. Each item opens a new analysis centered on that subject.
Overview
- Computing
- Data structure
- Immutable Immutable object
- Logical Logic programming
- Functional programming
- Amortized time Amortized analysis
- Array Array data structure
- Access time
- Van Emde Boas tree
- Lookup
- Potential function Potential method
- Source code
Partial versus full persistence
- Linear ordering Total order
- Performance characteristics Computer performance
- Rope data structure Rope (data structure)
Techniques for preserving previous versions
- Array Mutable array
- Copy-on-write
- Pointer Pointer (computer programming)
- Sleator Daniel Sleator
- Tarjan Robert Tarjan
- Linked data structure
- Sorted array
- Algorithm
Examples of persistent data structures
- Purely functional data structures Purely functional data structure
- Linked lists Linked list
- Reference
- Red–black trees Red–black tree
- Stacks Stack (data structure)
- Treaps Treap
- Queues Queue (abstract data type)
- Dequeues Double-ended queue
- Min-deques Min-deque?action=edit&redlink=1
- Random-access deques Random-access deque?action=edit&redlink=1
- Random access
- ML ML programming language
- Haskell Haskell (programming language)
- Garbage collection Garbage collection (computer science)
- Lisp Lisp (programming language)
- Racket Racket (programming language)
- Binary search tree
- Recursive Recursion
- Invariant Invariant (computer science)
- Binary tree
- Hash array mapped trie
- Phil Bagwell
- Hash tables Hash table
- Rich Hickey
- Clojure
- Tree Tree (data structure)
- Hash function
- Sparse array Sparse matrix
- Hash collisions Hash collision
- Branching factor
Usage in programming languages
- Pure functional language
- Referential transparency
- Java collections framework
- Value semantics
- Parallel computing
- Data races Data race
- Compare and swap Compare-and-swap
- Elm programming language Elm (programming language)
- Virtual DOM Document Object Model
- JavaScript
- React React (JavaScript library)
- Ember Ember.js
- Angular Angular (application platform)
- Java programming language Java (programming language)
- Flux architecture Flux architecture?action=edit&redlink=1
- JavaScript library
- Redux Redux (JavaScript library)
Garbage collection
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.
How this topic connects Entity context
Quick relationship hints grouped by predicate. Useful for spotting recurring semantic connections around the current entity.See the strongest relationship patterns around the current topic before diving into the raw triples.
Persistent data structure
Top relations
related to JavaScript · 16
Persistent data structure → As, Clojure, Elm, Flux, Immer, Immutable, It, JavaScript, Mori, One, React, Redux, Scala, The, The Redux, This
related to Examples of persistent data structures · 7
Persistent data structure → Many, Perhaps, Purely, So, Some, The, This
related to Clojure · 6
Persistent data structure → Clojure, Java, Like, Lisp, The, These
related to Prolog · 6
Persistent data structure → Delayed, Extensions, Prolog, Some Prolog, Their, There
related to Copy-on-write · 5
Persistent data structure → Bu, Copy-on-write, One, Theta, This
related to Next element search or point location · 4
Persistent data structure → Assume, Next Element Search, One, We
related to Scala · 4
Persistent data structure → Clojure, Object-Functional Style, Scala, The Scala
related to Garbage collection · 2
Persistent data structure → Because, In
is a · 1
Persistent data structure → singly linked list or cons-based list
Important terminology Word statistics
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Important terminology
data persistent structure node new time one modification structures displaystyle tree array version nodes table copy box path using used
Entity relationships Subject–Predicate–Object triples
Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Persistent data structure | is a | singly linked list or cons-based list | 0.90 | text |
| an array to store the data in the data structure | instance of | Techniques for preserving previous versionsCopy-on-writeOne method for creating a persistent data structure is to use a platform provided ephemeral data structure | 0.80 | text |
| copy the entirety of that data structure | instance of | Techniques for preserving previous versionsCopy-on-writeOne method for creating a persistent data structure is to use a platform provided ephemeral data structure | 0.80 | text |
| an array to store the data in the data structure | instance of | time Copy-on-writeOne method for creating a persistent data structure is to use a platform provided ephemeral data structure | 0.80 | text |
| copy the entirety of that data structure | instance of | time Copy-on-writeOne method for creating a persistent data structure is to use a platform provided ephemeral data structure | 0.80 | text |
| binary search trees | instance of | time Generalized form of persistencePath copying is one of the simple methods to achieve persistency in a certain data structure | 0.80 | text |
| reference counting or mark | instance of | Garbage collectionBecause persistent data structures are often implemented in such a way that successive versions of a data structure share underlying memory ergonomic use of su… | 0.80 | text |
| sweep | instance of | Garbage collectionBecause persistent data structures are often implemented in such a way that successive versions of a data structure share underlying memory ergonomic use of su… | 0.80 | text |
| Persistent data structure | related to Clojure | Like | 0.60 | section |
| Persistent data structure | related to Clojure | Lisp | 0.60 | section |
| Persistent data structure | related to Clojure | Clojure | 0.60 | section |
| Persistent data structure | related to Clojure | These | 0.60 | section |
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Related concept clusters Concept neighborhoods
Clusters of nearby vocabulary surrounding the topic. Scan them for adjacent concepts and language you may have missed.These clusters group vocabulary that occurs around closely connected concepts in the source material.
Connections between topic areas Semantic bridges
Bridge nodes connect otherwise separate parts of the map. Expand a row to inspect the topic groups on each side.Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.Persistent data structure
Nodes81
Edges80
Triples58
Avg. degree1.98
Density0.024691
Components1
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