Interpreter (computing)

In computer science, an interpreter is a computer program that directly executes instructions written in a programming or scripting language, without requiring them previously to have been compiled into a machine language program. An interpreter generally uses one of the following strategies for program execution: Parse the source code and perform its behavior directly; Translate source code into some efficient intermediate representation or object code and immediately execute that; Explicitly execute stored precompiled bytecode made by a compiler and matched with the interpreter Virtual Machine. Early versions of Lisp programming language and minicomputer and microcomputer BASIC dialects would be examples of the first type. Perl, Raku, Python, MATLAB, and Ruby are examples of the second, while UCSD Pascal is an example of the third type. Source programs are compiled ahead of time and stored as machine independent code, which is then linked at run-time and executed by an interpreter and/or compiler (for JIT systems). Some systems, such as Smalltalk and contemporary versions of BASIC and Java may also combine two and three. Interpreters of various types have also been constructed for many languages traditionally associated with compilation, such as Algol, Fortran, Cobol, C and C++. While interpretation and compilation are the two main means by which programming languages are implemented, they are not mutually exclusive, as most interpreting systems also perform some translation work, just like compilers. The terms "interpreted language" or "compiled language" signify that the canonical implementation of that language is an interpreter or a compiler, respectively. A high-level language is ideally an abstraction independent of particular implementations. Interpreters were used as early as 1952 to ease programming within the limitations of computers at the time (e.g. a shortage of program storage space, or no native support for floating point numbers).

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (1)

Related people (2)

Related concepts (169)

Related courses (25)

Related lectures (93)

Related MOOCs (1)

CauseOccam: Learning Interpretable Abstract Representations in Reinforcement Learning Environments via Model Sparsity

Sergei Volodin

"I choose this restaurant because they have vegan sandwiches" could be a typical explanation we would expect from a human. However, current Reinforcement Learning (RL) techniques are not able to provi

2021

CS-320: Computer language processing

We teach the fundamental aspects of analyzing and interpreting computer languages, including the techniques to build compilers. You will build a working compiler from an elegant functional language in

ENG-466: Distributed intelligent systems

The goal of this course is to provide methods and tools for modeling distributed intelligent systems as well as designing and optimizing coordination strategies. The course is a well-balanced mixture

CS-210: Functional programming

Understanding of the principles and applications of functional programming, the fundamental models of program execution, application of fundamental methods of program composition, meta-programming thr

Understanding Microcontrollers

Ce cours donne les bases théoriques et pratiques nécessaires à une bonne compréhension et utilisation des microcontrôleurs. De nombreux exemples seront abordés. Des exercices seront proposés, compatib

High-level programming language

In computer science, a high-level programming language is a programming language with strong abstraction from the details of the computer. In contrast to low-level programming languages, it may use natural language elements, be easier to use, or may automate (or even hide entirely) significant areas of computing systems (e.g. memory management), making the process of developing a program simpler and more understandable than when using a lower-level language. The amount of abstraction provided defines how "high-level" a programming language is.

Type system

In computer programming, a type system is a logical system comprising a set of rules that assigns a property called a type (for example, integer, floating point, string) to every "term" (a word, phrase, or other set of symbols). Usually the terms are various constructs of a computer program, such as variables, expressions, functions, or modules. A type system dictates the operations that can be performed on a term. For variables, the type system determines the allowed values of that term.

Object-oriented programming

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.

Bitcoin and Ethereum: Scripting and Gas

Explores Bitcoin scripting, Ethereum gas, smart contracts, limitations, and common uses.

Model Interpretation and Compilation

Explores model interpretation, compilation via partial evaluation, function calls, and the transition to partial evaluation, emphasizing the importance of model interpreters in supporting modeling languages.

Python Programming: File Handling and Exceptions

Explores file handling and exceptions in Python programming, covering reading, writing, and error handling strategies.