SML/NJ

SML/NJ

SML/NJ is a compiler and interactive environment for Standard ML, a general-purpose functional programming language. It emphasizes high performance, modularity, and portability.
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SML/NJ: Compiler and Interactive Environment

A compiler and interactive environment for Standard ML, emphasizing high performance, modularity, and portability.

What is SML/NJ?

SML/NJ (Standard ML of New Jersey) is an open-source compiler and interactive environment for the Standard ML programming language. Developed at Bell Labs, SML/NJ emphasizes high performance, modularity, and portability across platforms.

As a functional language, Standard ML features immutable data structures, pattern matching, higher-order functions, type inference, and a module system. The compiler uses advanced compilation techniques for efficient native code generation.

The SML/NJ interactive environment provides a read-eval-print loop for evaluating Standard ML expressions. It integrates a debugger, profiler, and support for multiple threads. The build system and package manager make it easy to develop larger applications.

Key features of SML/NJ include:

  • Compiles Standard ML code to efficient native machine code
  • Advanced module system for building modular and reusable code
  • Automatic type inference frees programmers from specifying types
  • Supports concurrency and multi-threaded programming
  • Interactive environment for rapid testing and debugging

With its strong theoretical foundations and focus on high performance, SML/NJ is widely used in academia, research, and industry applications requiring reliable and efficient code.

SML/NJ Features

Features

  1. Compiler for Standard ML
  2. Interactive environment
  3. Support for modules
  4. Automatic memory management
  5. Polymorphic type inference
  6. High performance code generation
  7. Portability across platforms

Pricing

  • Open Source

Pros

Clean, elegant language design

Strong static typing catches errors early

Functional programming paradigm prevents bugs

Modules encourage code reuse

Type inference reduces boilerplate

Fast execution for a functional language

Cons

Not as popular/widespread as other languages

Limited libraries compared to other languages

Steep learning curve for imperative programmers

REPL not as fully featured as some other languages

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