Oz programming language |
Oz is a multi-paradigm programming language.
Oz was originally developed in the Programming Systems Lab at Saarland University by Gert Smolka and his students in the early 1990s. Since 1999, Oz has been continually developed by an international group, the Mozart Consortium , that originally consisted of Saarland University, the Swedish Institute of Computer Science, and the Université catholique de Louvain. In 2005, the responsibility for managing Mozart development was transferred to a core group, the Mozart Board , with the express purpose of opening Mozart development to a larger community.
Oz has a high-quality implementation, the Mozart Programming System, which is released with an Open Source license by the Mozart Consortium. Mozart has been ported to different flavors of Unix, FreeBSD, Linux, Microsoft Windows, and Mac OS X.
=Language features=
Oz contains in a simple and well-factored way most of the concepts of the major programming paradigms, including logic programming, functional programming (both lazy evaluation and eager evaluation), imperative programming, object oriented programming, Constraint programming, Distributed programming, and concurrent programming language programming. Oz has both a simple formal semantics (see chapter 13 of the book mentioned below) and an efficient implementation, the Mozart Programming System (see below). Oz is a Concurrency (computer science) language, as the term was introduced by Joe Armstrong, the main designer of the Erlang programming language. A concurrency-oriented language makes Concurrency (computer science) both easy to use and efficient.
In addition to multi-paradigm programming, the major strengths of Oz are in constraint programming and distributed programming. Because of its factored design, Oz is able to successfully implement a network-transparent distributed programming model. This model makes it easy to program open, Fault tolerant applications within the language. For constraint programming, Oz introduces the idea of computation spaces, which allows user-defined search and distribution strategies that are Orthogonal#Derived_meanings to the constraint domain.
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