Research any topic before you write.

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

Ruby MRI

Matz's Ruby Interpreter or Ruby MRI (also called CRuby) is an implementation of the Ruby programming language named after Ruby creator Yukihiro Matsumoto ("Matz"). Until the specification of the Ruby language in 2012, the MRI implementation was considered the de facto reference. Starting with Ruby 1.9, and continuing with Ruby 2.x and above, the official…

History & Art

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 Ruby MRI. 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.

Operating systems

21 related topics

History

2 related topics

Licensing terms

6 related topics

Limitations

1 related topics

Key facts & relationships

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

Developer
Yukihiro Matsumoto (among others)
Final release
1.8.7 / {May 31, 2008; 18 years ago (2008-05-31)
License
Ruby License Simplified BSD License GNU General Public License (prior to 1.9.3)
Operating system
Cross-platform
Release
August 4, 2003; 23 years ago (2003-08-04)
Repository
git.ruby-lang.org/ruby.git

Topics to explore

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

Overview

History

Licensing terms

Operating systems

Limitations

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

Ruby MRI

Nodes41
Edges40
Triples15
Avg. degree1.95
Density0.04878
Components1

How this topic connects Entity context

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

Ruby MRI

Top relations

related to Operating systems · 5
Ruby MRI → Acorn RISC OSAmigaBeOS, HaikuMS-DOSIBM, OSBlue Gene/L, Ruby, Tablet OSLinuxOS XWindowsWindows CEMorphOSOS/2OpenVMSSyllableSymbian
Developer · 1
Ruby MRI → Yukihiro Matsumoto (among others)
Final release · 1
Ruby MRI → 1.8.7 / {May 31, 2008; 18 years ago (2008-05-31)
License · 1
Ruby MRI → Ruby License Simplified BSD License GNU General Public License (prior to 1.9.3)
Operating system · 1
Ruby MRI → Cross-platform
Release · 1
Ruby MRI → August 4, 2003; 23 years ago (2003-08-04)
Repository · 1
Ruby MRI → git.ruby-lang.org/ruby.git
Successor · 1
Ruby MRI → YARV
Type · 1
Ruby MRI → Ruby programming language interpreter
Website · 1
Ruby MRI → www.ruby-lang.org

Important terminology Word statistics

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

Important terminology

ruby mri interpreter language yarv also implementation programming yukihiro matsumoto operating release license public named matz reference official version systems

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Ruby MRIDeveloperYukihiro Matsumoto (among others)1.00infobox
Ruby MRIFinal release1.8.7 / {May 31, 2008; 18 years ago (2008-05-31)1.00infobox
Ruby MRILicenseRuby License Simplified BSD License GNU General Public License (prior to 1.9.3)1.00infobox
Ruby MRIOperating systemCross-platform1.00infobox
Ruby MRIReleaseAugust 4, 2003; 23 years ago (2003-08-04)1.00infobox
Ruby MRIRepositorygit.ruby-lang.org/ruby.git1.00infobox
Ruby MRISuccessorYARV1.00infobox
Ruby MRITypeRuby programming language interpreter1.00infobox
Ruby MRIWebsitewww.ruby-lang.org1.00infobox
Ruby MRIWritten inC1.00infobox
Ruby MRIrelated to Operating systemsRuby0.60section
Ruby MRIrelated to Operating systemsAcorn RISC OSAmigaBeOS0.60section

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.