In computer science, a dynamic programming language is a class of high-level programming languages, which at runtime execute many common programming behaviours that static programming languages perform during compilation. These behaviors could include an extension of the program, by adding new code, by extending objects and definitions, or by modifying the type system. Although similar behaviors can be emulated in nearly any language, with varying degrees of difficulty, complexity and performance costs, dynamic languages provide direct tools to make use of them. Many of these features were first implemented as native features in the Lisp programming language.
Most dynamic languages are also dynamically typed, but not all are. Dynamic languages are frequently (but not always) referred to as scripting languages, although that term in its narrowest sense refers to languages specific to a given run-time environment.
Some dynamic languages offer an eval function. This function takes a string or abstract syntax tree containing code in the language and executes it. If this code stands for an expression, the resulting value is returned. Erik Meijer and Peter Drayton distinguish the runtime code generation offered by eval from the dynamic loading offered by shared libraries, and warn that in many cases eval is used merely to implement higher-order functions (by passing functions as strings) or deserialization.
A type or object system can typically be modified during runtime in a dynamic language. This can mean generating new objects from a runtime definition or based on mixins of existing types or objects. This can also refer to changing the inheritance or type tree, and thus altering the way that existing types behave (especially with respect to the invocation of methods).
As a lot of dynamic languages come with a dynamic type system, runtime inference of types based on values for internal interpretation marks a common task. As value types may change throughout interpretation, it is regularly used upon performing atomic operations.
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The students will acquire a solid knowledge on the processes necessary to design, write and use scientific software. Software design techniques will be used to program a multi-usage particles code, ai
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Julia is a high-level, general-purpose dynamic programming language. Its features are well suited for numerical analysis and computational science. Distinctive aspects of Julia's design include a type system with parametric polymorphism in a dynamic programming language; with multiple dispatch as its core programming paradigm. Julia supports concurrent, (composable) parallel and distributed computing (with or without using MPI or the built-in corresponding to "OpenMP-style" threads), and direct calling of C and Fortran libraries without glue code.
Object-Oriented Programming (OOP) is a programming paradigm based on the concept of "objects", which can contain data and code. The data is in the form of fields (often known as attributes or properties), and the code is in the form of procedures (often known as methods). A common feature of objects is that procedures (or methods) are attached to them and can access and modify the object's data fields. In this brand of OOP, there is usually a special name such as or used to refer to the current object.
Programming languages are used for controlling the behavior of a machine (often a computer). Like natural languages, programming languages follow rules for syntax and semantics. There are thousands of programming languages and new ones are created every year. Few languages ever become sufficiently popular that they are used by more than a few people, but professional programmers may use dozens of languages in a career. Most programming languages are not standardized by an international (or national) standard, even widely used ones, such as Perl or Standard ML (despite the name).
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