Research any topic before you write.

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

CLU (programming language)

CLU is a class-based programming language created at the Massachusetts Institute of Technology (MIT) by Barbara Liskov and her students starting in 1973. While it did not find extensive use, it introduced many features that are used widely now, and is seen as a step in the development of object-oriented programming (OOP).

Art & Technology

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 CLU (programming language). 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.

Key facts & relationships

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

Designed by
Barbara Liskov and her students
Developer
Massachusetts Institute of Technology
First appeared
1975; 51 years ago (1975)
Paradigm
Multi-paradigm: class-based, procedural
Stable release
Native CLU 1.5 (SPARC, VAX) / May 26, 1989; 37 years ago (1989-05-26) Portable CLU / November 6, 2009; 16 years ago (2009-11-06)
Typing discipline
Strong

Topics to explore

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

Overview

Clusters

Other features

Influence

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

CLU (programming language)

Nodes39
Edges38
Triples11
Avg. degree1.95
Density0.051282
Components1

How this topic connects Entity context

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

CLU (programming language)

Top relations

Designed by · 1
CLU (programming language) → Barbara Liskov and her students
Developer · 1
CLU (programming language) → Massachusetts Institute of Technology
First appeared · 1
CLU (programming language) → 1975; 51 years ago (1975)
Paradigm · 1
CLU (programming language) → Multi-paradigm: class-based, procedural
Stable release · 1
CLU (programming language) → Native CLU 1.5 (SPARC, VAX) / May 26, 1989; 37 years ago (1989-05-26) Portable CLU / November 6, 2009; 16 years ago (2009-11-06)
Typing discipline · 1
CLU (programming language) → Strong
Website · 1
CLU (programming language) → pmg.csail.mit.edu/CLU.html

Important terminology Word statistics

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

Important terminology

clu languages iterators assignment type language data types multiple return values programming python cluster exception type-safe also use first barbara

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
CLU (programming language)Designed byBarbara Liskov and her students1.00infobox
CLU (programming language)DeveloperMassachusetts Institute of Technology1.00infobox
CLU (programming language)First appeared1975; 51 years ago (1975)1.00infobox
CLU (programming language)ParadigmMulti-paradigm: class-based, procedural1.00infobox
CLU (programming language)Stable releaseNative CLU 1.5 (SPARC, VAX) / May 26, 1989; 37 years ago (1989-05-26) Portable CLU / November 6, 2009; 16 years ago (2009-11-06)1.00infobox
CLU (programming language)Typing disciplineStrong1.00infobox
CLU (programming language)Websitepmg.csail.mit.edu/CLU.html1.00infobox
integersinstance ofthe latter being base types0.80text
booleansinstance ofthe latter being base types0.80text
charactersinstance ofthe latter being base types0.80text
stringsinstance ofthe latter being base types0.80text

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.