Oz is a multiparadigm programming language, developed in the Programming Systems Lab at Université catholique de Louvain, for programming-language education. It has a canonical textbook: Concepts, Techniques, and Models of Computer Programming. Oz was first designed by Gert Smolka and his students in 1991. In 1996, development of Oz continued in cooperation with the research group of Seif Haridi and Peter Van Roy at the Swedish Institute of Computer Science. Since 1999, Oz has been continually developed by an international group, the Mozart Consortium, which 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. The Mozart Programming System is the primary implementation of Oz. It is released with an open source license by the Mozart Consortium. Mozart has been ported to Unix, FreeBSD, Linux, Windows, and macOS.
Language features Oz contains most of the concepts of the major programming paradigms, including logic, functional (both lazy evaluation and eager evaluation), imperative, object-oriented, constraint, distributed, and concurrent programming. Oz has both a simple formal semantics (see chapter 13 of the book mentioned below) and an efficient implementation. Oz is a concurrency-oriented language, as the term was introduced by Joe Armstrong, the main designer of the Erlang language. A concurrency-oriented language makes concurrency easy to use and efficient. Oz supports a canonical graphical user interface (GUI) language QTk. In addition to multi-paradigm programming, the major strengths of Oz are in constraint programming and distributed programming. Due to 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 allow user-defined search and distribution strategies orthogonal to the constraint domain.
Language overview
Data structures Oz is based on a core language with very few datatypes that can be extended into more practical ones through syntactic sugar. Basic data structures:
Numbers: floating point or integer (real integer) Records: for grouping data : circle(x:0 y:1 radius:3 color:blue style:dots). Here the terms x,y, radius etc. are called features and the data associated with the features (in this case 0,1,3 etc.) are the values. Tuples: Records with integer features in ascending order: circle(1:0 2:1 3:3 4:blue 5:dots) . Lists: a simple linear structure
Those data structures are values (constant), first class and dynamically type checked. Variable names in Oz start with an uppercase letter to distinguish them from literals which always begin with a lowercase letter.
Functions Functions are first class values, allowing higher order functional programming:
Functions may be used with both free and bound variables. Free variable values are found using static lexical scoping.
Higher-order programming Functions are like other Oz objects. A function can be passed as an attribute to other functions or can be returned in a function.
Anonymous functions Like many other functional languages, Oz supports use of anonymous functions (i.e. functions which do not have a name) with higher order programming. The symbol $ is used to denote these. In the following, the square function is defined anonymously and passed, causing [1 4 9] to be browsed.
Since anonymous functions don't have names, it is not possible to define recursive anonymous functions.
Procedures Functions in Oz are supposed to return a value at the last statement encountered in the body of the function during its execution. In the example below, the function Ret returns 5 if X > 0 and -5 otherwise.
But Oz also provides a facility in case a function must not return values. Such functions are called procedures. Procedures are defined using the construct "proc" as follows
The above example doesn't return any value, it just prints 5 or -5 in the Oz browser depending on the sign of X.
Dataflow variables and declarative concurrency When the program encounters an unbound variable it waits for a value. For example, below, the thread will wait until both X and Y are bound to a value before showing the value of Z.
The value of a dataflow variable cannot be changed once it is bound:
Dataflow variables make it easy to create concurrent stream agents:
Because of the way dataflow variables work, it is possible to put threads anywhere in a program and guaranteed that it will have the same result. This makes concurrent programming very easy. Threads are very cheap: it is possible to have 100,000 threads running at once.
Example: Trial division sieve This example computes a stream of prime numbers using the trial division algorithm by recursively creating concurrent stream agents that filter out non-prime numbers:
Laziness Oz uses eager evaluation by default, but lazy evaluation is possible. Below, the fact is only computed when value of X is needed to compute the value of Y.
Lazy evaluation gives the possibility of storing truly infinite data structures in Oz. The power of lazy evaluation can be seen from the following code sample:
The code above elegantly computes all the Regular Numbers in an infinite list. The actual numbers are computed only when they are needed.
Message passing concurrency The declarative concurrent model can be extended with message passing via simple semantics:
With a port and a thread, asynchronous agents can be defined:
State and objects It is again possible to extend the declarative model to support state and object-oriented programming with very simple semantics. To create a new mutable data structure called Cells:
With these simple semantic changes, the whole object-oriented paradigm can be supported. With a little syntactic sugar, OOP becomes well integrated in Oz.
Execution speed The execution speed of a program produced by the Mozart compiler (version 1.4.0 implementing Oz 3) is very slow. On a 2012 set of benchmarks it averaged about 50 times slower than that of the GNU Compiler Collection (GCC) for the C language.
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