Multi-paradigm programming language

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A multi-paradigm programming language is a programming language that supports more than one programming paradigm. As Leda designer Tim Budd holds it: The idea of a multiparadigm language is to provide a framework in which programmers can work in a variety of styles, freely intermixing constructs from different paradigms. The design goal of such languages is to allow programmers to use the best tool for a job, admitting that no one paradigm solves all problems in the easiest or most efficient way.

An example is Oz, which has subsets that are a logic language (Oz descends from logic programming), a functional language, an object-oriented language, a dataflow concurrent language, and more. Oz was designed over a ten-year period to combine in a harmonious way concepts that are traditionally associated with different programming paradigms.

1 Multiparadigm languages
2 See also
3 References

Multiparadigm languages

Languages can be grouped by the number and types of paradigms supported.

Paradigm summaries

This only serves for quick reference for programming paradigms listed here

Dataflow - forced recalculation of formulas when data values change (e.g. Spreadsheets)
Visual programming language - manipulating program elements graphically rather than by specifying them textually (e.g. Simulink)
Declarative programming - describes actions (e.g. HTML describe a page but not how to actually display it)
Imperative programming - explicit statements that change a program state
Functional programming - uses evaluation of mathematical functions and avoids state and mutable data
Object-Oriented programming - uses classes and instances, inheritance, encapsulation and polymorphism
Prototype-based programming - object-oriented programming that avoids classes and implements inheritance via the cloning of instances
Parallel computing - simultaneous execution with the necessary communication and synchronization between processes/threads
Actor model - concurrent computation with "actors" that makes local decisions in response to the environment (capable of selfish or competitive behavior)
Pipeline programming - no nested function calls, but a simple flow structures with easy to visualize/understand data flow through the program
Constraint programming - relations between variables are expressed as constraints (or constraint networks), directing allowable solutions (uses constraint satisfaction or simplex algorithm)
Rule-based programming - a network of rules of thumb that comprise a knowledge base and can be used for expert systems and problem deduction & resolution
Logic programming - uses logical facts to create a model that can prove consistency, deduce further truths or answer questions about the model (e.g. Dogs are animals! Dogs are red! Are some animals red?)
Reflective programming - special case of metaprogramming (modification of programs as data by another program or ability to do part of the work in compile time instead of running time) in which the program modifies or extends itself

References

^ PHP Manual, Chapter 17. Functions
^ PHP Manual, Chapter 19. Classes and Objects (PHP 5)
^ Charming Python: Functional programming in Python, Part 1
^ The Little JavaScripter demonstrates fundamental commonality with Scheme, a functional language.
^ Object Oriented Programming in JavaScript gives an overview of object-oriented programming techniques in JavaScript.
^ Martin Odersky et al, An Overview of the Scala Programming Language, 2nd Edition
^ Ada Reference Manual, ISO/IEC 8652:2005(E) Ed. 3, Section 9: Tasks and Synchronization
^ Ada Reference Manual, ISO/IEC 8652:2005(E) Ed. 3 Annex E: Distributed Systems
^ Ada Reference Manual, ISO/IEC 8652:2005(E) Ed. 3, Section 12: Generic Units
^ Ada Reference Manual, ISO/IEC 8652:2005(E) Ed. 3, Section 6: Subprograms
^ Ada Reference Manual, ISO/IEC 8652:2005(E) Ed. 3, 3.9 Tagged Types and Type Extensions

Multiparadigm Design for C++, by Jim Coplien, 1998.
Concepts, Techniques, and Models of Computer Programming, by Peter Van Roy and Seif Haridi, 2004.