Fortran

Description

Fortran (short for "Formula Translation") is a high-level programming language that is particularly well-suited for numerical computation and scientific computing. It was one of the earliest programming languages and remains in use today for applications that require intensive numerical calculations, such as weather forecasting, computational fluid dynamics, and computational physics.

History

1. 1950s: Creation and Early Development

   • 1954-1957: Fortran was developed by IBM, led by John Backus. The first version, Fortran I, was released in 1957 for the IBM 704 computer.

   • 1958: Fortran II was introduced, adding support for procedural programming with subroutines and functions.

2. 1960s: Standardization and Expansion

   • 1962: Fortran IV was released, which became widely adopted and led to the first standardization effort.

   • 1966: The first official standard, Fortran 66, was published by the American National Standards Institute (ANSI).

3. 1970s: Further Enhancements

   • 1978: Fortran 77 was introduced, adding features like structured programming constructs (e.g., IF-THEN-ELSE), character string handling, and improved I/O capabilities.

4. 1990s: Modernization

   • 1991: Fortran 90 was released, introducing modern programming concepts such as modules, array programming, recursion, and dynamic memory allocation.

   • 1997: Fortran 95 followed, adding minor improvements and clarifications to Fortran 90.

5. 2000s: Continued Evolution

   • 2004: Fortran 2003 was introduced, adding object-oriented programming features, interoperability with C, and improved support for parallel computing.

   • 2010: Fortran 2008 was released, further enhancing parallel computing capabilities with coarrays and other features.

6. 2018: Latest Standard

   • 2018: Fortran 2018 was published, incorporating additional features for parallel and concurrent programming, as well as further refinements and updates.

Summary

Fortran has evolved significantly since its inception in the 1950s, adapting to new programming paradigms and computational needs. It remains a powerful tool for scientific and engineering applications, thanks to its efficiency in numerical computation and extensive legacy codebase.