Research any topic before you write.

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

Packrat parser

The Packrat parser is a type of parser that shares similarities with the recursive descent parser in its construction. However, it differs because it takes parsing expression grammars (PEGs) as input rather than LL grammars.

Syntax, Memoization technique & Overview

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 Packrat parser. 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.

Syntax

2 related topics

Memoization technique

2 related topics

Overview

11 related topics

Key facts & relationships

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

Average performance
O ( n ) {\displaystyle O(n)}
Best-case performance
O ( n ) {\displaystyle O(n)}
Class
Parsing grammars that are PEG
Data structure
String
Worst-case performance
O ( n ) {\displaystyle O(n)} or O ( n 2 ) {\displaystyle O(n^{2})} without special handling of iterative combinator
Worst-case space complexity
O ( n ) {\displaystyle O(n)}

Topics to explore

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

Overview

Syntax

Memoization technique

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

Packrat parser

Nodes19
Edges18
Triples28
Avg. degree1.89
Density0.105263
Components1

How this topic connects Entity context

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

Packrat parser

Top relations

related to Cut operator · 7
Packrat parser → Another, By, For, However, Packrat, This, When
related to Left recursion · 7
Packrat parser → During, If, Left, Nonetheless, Packrat, Since Packrat, This
related to Iterative combinator · 4
Packrat parser → Packrat, The, This, With
related to Syntax · 3
Packrat parser → PEG, PEGs, The
Average performance · 1
Packrat parser → O ( n ) {\displaystyle O(n)}
Best-case performance · 1
Packrat parser → O ( n ) {\displaystyle O(n)}
Class · 1
Packrat parser → Parsing grammars that are PEG
Data structure · 1
Packrat parser → String
Worst-case performance · 1
Packrat parser → O ( n ) {\displaystyle O(n)} or O ( n 2 ) {\displaystyle O(n^{2})} without special handling of iterative combinator
Worst-case space complexity · 1
Packrat parser → O ( n ) {\displaystyle O(n)}

Important terminology Word statistics

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

Important terminology

packrat parsing parser displaystyle input pegs grammar string memoization matrix ts results time recursion space expression gtdpl operators left cut

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Packrat parserAverage performanceO ( n ) {\displaystyle O(n)}1.00infobox
Packrat parserBest-case performanceO ( n ) {\displaystyle O(n)}1.00infobox
Packrat parserClassParsing grammars that are PEG1.00infobox
Packrat parserData structureString1.00infobox
Packrat parserWorst-case performanceO ( n ) {\displaystyle O(n)} or O ( n 2 ) {\displaystyle O(n^{2})} without special handling of iterative combinator1.00infobox
Packrat parserWorst-case space complexityO ( n ) {\displaystyle O(n)}1.00infobox
Packrat parseris atype of parser that shares similarities with the recursive descent parser in its construction0.90text
Packrat parserrelated to Cut operatorAnother0.60section
Packrat parserrelated to Cut operatorPackrat0.60section
Packrat parserrelated to Cut operatorThis0.60section
Packrat parserrelated to Cut operatorFor0.60section
Packrat parserrelated to Cut operatorWhen0.60section

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.