Interpreted Language

An interpreted language is a programming language for which most of its implementations execute instructions directly, without previously compiling a program into machine-language instructions. The interpreter executes the program directly, translating each statement into a sequence of one or more subroutines already compiled into machine code.

The terms interpreted language and compiled language are not well defined because, in theory, any programming language can be either interpreted or compiled. In modern programming language implementation it is increasingly popular for a platform to provide both options.

Interpreted languages can also be contrasted with machine languages. Functionally, both execution and interpretation mean the same thing -- fetching the next instruction/statement from the program and executing it. Although interpreted byte code is additionally identical to machine code in form and has an assembler representation, the term "interpreted" is practically reserved for "software processed" languages (by virtual machine or emulator) on top of the native (i.e. hardware) processor.

In principle, programs in many languages may be compiled or interpreted, emulated or executed natively, so this designation is applied solely based on common implementation practice, rather than representing an essential property of a language.

Many languages have been implemented using both compilers and interpreters, including BASIC, C, Lisp, Pascal, and Python. Java and C# are compiled into bytecode, the virtual machine-friendly interpreted language. Lisp implementations can freely mix interpreted and compiled code.

Historical background

In the early days of computing, language design was heavily influenced by the decision to use compiling or interpreting as a mode of execution. For example, Smalltalk (1980), which was designed to be interpreted at run-time, allows generic objects to dynamically interact with each other.

Initially, interpreted languages were compiled line-by-line; that is, each line was compiled as it was about to be executed, and if a loop or subroutine caused certain lines to be executed multiple times, they would be recompiled every time. This has become much less common. Most so-called interpreted languages use an intermediate representation, which combines compiling and interpreting.

Examples include:

The intermediate representation can be compiled once and for all (as in Java), each time before execution (as in Perl or Ruby), or each time a change in the source is detected before execution (as in Python).


Interpreting a language gives implementations some additional flexibility over compiled implementations. Features that are often easier to implement in interpreters than in compilers include:

Furthermore, source code can be read and copied, giving users more freedom.


Disadvantages of interpreted languages are:

  • Without static type-checking, which is usually performed by a compiler, programs can be less reliable, because type checking eliminates a class of programming errors.
  • Interpreters can be susceptible to Code injection attacks.
  • Slower execution compared to direct native machine code execution on the host CPU. A technique used to improve performance is just-in-time compilation which converts frequently executed sequences of interpreted instruction to host machine code. JIT is most often combined with compilation to byte-code as in Java.
  • Source code can be read and copied (e.g. JavaScript in web pages), or more easily reverse engineered through reflection in applications where intellectual property has a commercial advantage. In some cases obfuscation can be used to encrypt source code or obscure its purpose.

List of frequently used interpreted languages

Languages usually compiled to a bytecode

Many languages are first compiled to bytecode. ?ometimes, bytecode can also be compiled to a native binary using an AOT compiler or executed natively, by hardware processor.

See also


  • Brown, P.J. (1979). Writing Interactive Compilers and Interpreters. John Wiley. ISBN 0-471-27609-X. 

  This article uses material from the Wikipedia page available here. It is released under the Creative Commons Attribution-Share-Alike License 3.0.

Connect with defaultLogic
What We've Done
Led Digital Marketing Efforts of Top 500 e-Retailers.
Worked with Top Brands at Leading Agencies.
Successfully Managed Over $50 million in Digital Ad Spend.
Developed Strategies and Processes that Enabled Brands to Grow During an Economic Downturn.
Taught Advanced Internet Marketing Strategies at the graduate level.

Manage research, learning and skills at defaultLogic. Create an account using LinkedIn or facebook to manage and organize your IT knowledge. defaultLogic works like a shopping cart for information -- helping you to save, discuss and share.

  Contact Us