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OpenLisp: Standards, Technology & Applications
OpenLisp is a programming language in the Lisp family developed by Christian Jullien from Eligis. It conforms to the international standard for ISLISP published jointly by the International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC), ISO/IEC 13816:1997(E), revised to ISO/IEC 13816:2007(E).
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OpenLisp topic overview
The analysis highlights Standards, Technology and Applications as prominent areas in the source structure around OpenLisp.
Related topics
103
Source areas
11
Connected nodes
114
Extracted relationships
91
Concept neighborhoods
41
Bridge connections
114
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Standard libraries · 21 topics
Overview · 20 topics
Ports · 16 topics
Technology · 16 topics
Goals · 8 topics
User interface · 7 topics
Adoption · 5 topics
Origin of name · 5 topics
Compiler · 2 topics
License · 2 topics
Style guide · 1 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Designed by
Christian Jullien
Developer
Christian Jullien
Family
Lisp
First appeared
April 1988; 38 years ago (1988-04)
Implementation language
C, OpenLisp
License
Proprietary
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How OpenLisp connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around OpenLisp shows recurring relationship patterns in the source. For example, OpenLisp → CSV, Extensible Markup Language, FFI, Hypertext Transfer Protocol, ISLISP, JavaScript Object Notation, JSON, Lisp, MySQL, Odbc, POP3, Post Office Protocol, PostgreSQL, Rss, Simple Mail Transfer Protocol, SMTP, SQL, SQLite, Telnet, XML Another extracted example is OpenLisp → AIX, Cygwin, FreeBSD, HP-UX, Linux, MS-DOS, NetBSD, OpenBSD, OpenVMS, OS, OS/2, Pocket PC, POSIX, QNX, Solaris, The, Unix, Windows. Use these groups to spot repeated connection types before inspecting the individual relationships.
OpenLisp
Top relations
related to Connectors· 20
OpenLisp → CSV, Extensible Markup Language, FFI, Hypertext Transfer Protocol, ISLISP, JavaScript Object Notation, JSON, Lisp, MySQL, Odbc, POP3, Post Office Protocol, PostgreSQL, Rss, Simple Mail Transfer Protocol, SMTP, SQL, SQLite, Telnet, XML
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 91 structured relationships around OpenLisp. Examples in this analysis include OpenLisp → Designed by → Christian Jullien and OpenLisp → Family → Lisp. The table shows each extracted connection, where it came from and its confidence.
11.7.0 / 13 December 2022; 3 years ago (2022-12-13)
1.00
infobox
OpenLisp
Typing discipline
Dynamic, strong
1.00
infobox
OpenLisp
Website
christian.jullien.free.fr
1.00
infobox
OpenLisp
is a
programming language in the Lisp family developed by Christian Jullien from Eligis
0.90
text
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around OpenLisp bring nearby vocabulary together. In this analysis, examples include Language, Lisp and Implement. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
OpenLisp
Language
Lisp
Implement
Uses
Protocol
Windows
Emacs
Interface
System
Islisp
Christian
Family
openlisp
Language
Lisp
Implement
Uses
Protocol
Windows
Emacs
Interface
System
Islisp
Christian
Family
programming language
Lap
Lisp
Compiler
Christian
Family
Jullien
Openlisp
Interpreter
Libraries
Program
Protocol
Systems
lisp
Compiler
Code
Openlisp
Interface
Intermediate
Lap
Christian
Family
Jullien
Interpreter
Libraries
Written
christian jullien
Family
Jullien
License
Implementation
Standard
Language
Libraries
Memory
Name
Unix
Website
Windows
islisp
Interface
Implementation
Standard
Xml
Libraries
Protocol
Website
System
Language
License
Openlisp
Common
common lisp
Operating
Compiler
Implementation
Posix
Sql
Xml
Code
Openlisp
Libraries
Protocol
Runs
Written
compiler
Code
Intermediate
Lap
Lisp
Interpreter
Language
Libraries
License
Family
Implementation
Jullien
Standard
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For OpenLisp, one of the stronger structural bridges in this analysis connects OpenLisp with Standard libraries. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
OpenLisp
Nodes115
Edges114
Triples91
Avg. degree1.98
Density0.017391
Components1
Source & methodology
TTTA analyzes the structure around OpenLisp to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Standards, Technology & Applications, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
