Before high-level languages
In the early 1950s, scientists and engineers who wanted a computer to solve an equation had to translate it by hand into machine code or assembly language. That meant deciding where numbers lived in memory, how to move them in and out of registers, and how to repeat a calculation efficiently. The mathematics might take a page; the program could take much longer, and a program tied to one machine was not easily moved elsewhere.
Programmers at the time were also skeptical about automatic coding systems. Several early tools existed, but many produced slow programs, and machine time was expensive. Many working programmers felt that skilled hand coding would always beat a machine translation.
The IBM project
Around 1954, a small IBM group led by John Backus began designing a system to let users write mathematical formulas in a notation close to ordinary algebra. The name FORTRAN comes from “formula translation.” The team included several other programmers and mathematicians, and the work is best understood as a group project rather than the work of one person.
The goal was ambitious. The translator, the compiler, had to produce object code nearly as efficient as what a good programmer would write by hand. Otherwise, scientists would not accept it. Much of the project’s effort went into the compiler itself rather than the language grammar. The first version was delivered for the IBM 704 computer in the late 1950s, after taking longer than originally hoped, which was common for software projects even then.
What the language offered
A FORTRAN program could contain statements that looked like equations, along with loops, conditional statements and ways to read and print data. The language handled arithmetic with whole numbers and with real numbers (floating point), along with arrays, which were central for the tables of values used in numerical work.
For a physicist or engineer, this meant a calculation could be written in a few lines that resembled the original formula. A bridge-stress calculation, a trajectory or a table of values could be expressed in terms of the problem. The programmer still needed to understand numerical methods, since computers represent real numbers approximately, but the clerical effort was greatly reduced.
Why it spread
FORTRAN spread for several reasons that were practical rather than glamorous:
- Its compiler produced reasonably efficient code, which answered the main objection.
- Computer makers provided versions for their own machines, so users could move between systems with moderate effort.
- Libraries of mathematical routines were written in it, and those libraries were shared among researchers.
- Universities taught it to students in science and engineering.
A formal standard was developed in the 1960s, and later revisions over the following decades added structured programming and other features. Because the language was standardized, a program could be moved between machines more easily than with earlier tools, though vendor extensions meant that careful work was still needed.
Scientific computing grows around it
Numerical simulation, data reduction and engineering analysis all grew rapidly once programming became less laborious. Weather prediction, structural analysis and other kinds of computer simulation relied on numerical programs. FORTRAN was a common choice for such work, and it was used heavily on large machines, including those sometimes called supercomputers.
It would be an overstatement to say FORTRAN alone made these fields possible. Hardware improvements, new numerical methods and the work of scientists themselves were all essential. What the language did was lower the cost of turning a mathematical idea into a working program, which made computing available to more researchers. In that sense it was an important factor in the spread of scientific computing as a normal part of research.
Criticism and competition
FORTRAN was not without critics. Early versions had restrictions that felt awkward, such as fixed column layouts inherited from punched cards, and limited ways to organize large programs. Newer languages offered more flexible data structures and clearer control flow. Computer scientists interested in language design often preferred alternatives such as ALGOL, an international effort of the same era that strongly influenced later languages even though it was less widely used in practice.
Despite this, FORTRAN continued to be revised. Later versions modernized the syntax and added features for array handling and parallel computing. Debate continues about how it compares with newer languages for numerical work; this depends heavily on the task and the code base.
A long afterlife
One reason FORTRAN persists is the large body of existing code. Numerical libraries developed over decades have been tested thoroughly, and rewriting them risks introducing new errors. Researchers in some areas continue to maintain and extend such software.
Another lasting effect is conceptual. FORTRAN helped establish that a compiler for a high-level language could be efficient enough for serious use. The belief that one can describe a problem in human-friendly terms and rely on a translator for the rest shaped the languages that followed, from the business-oriented COBOL language to the modern tools used in data analysis.