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Staying at the cutting edge is a requirement for every programmer and developer nowadays. Learning the latest languages and keeping up to date on the most popular ones will give any developer a competitive edge in a professional environment. However, there are some exceptions to this rule; namely ‘COBOL’ and ‘Fortran’.
These great grandfathers of programming languages have been around since the 60s, and somehow are still in use today. From powering the mainframes behind bank transactions to conducting astrophysics simulations, COBOL and Fortran refuse to die. These languages are widely utilised in both the financial and scientific fields respectively and while many have sounded the alarm that these languages are beginning their downturn, here’s why COBOL and Fortran will not die out for the foreseeable future.
COBOL: The Programming Language that Refuses to Retire
Today, we can’t imagine a world without Internet-powered banking but that was the world COBOL was born into. Standing for Common Business Oriented Language, COBOL was created in 1959 to run on the mainframe computers of the time. It was one of the building blocks that made up the first generation of computer software for businesses, and was largely created without the involvement of computer scientists and academicians. This resulted in a language created from the ground up for running business calculations on mainframe computers.
The language was designed for applications deployed in data processing and mainly for transaction processing systems. Many early systems for ticket reservations, booking, healthcare, and tax processing were built on COBOL. These systems used punch cards as the input for the mainframe, leading to COBOL’s reputation as one of the first languages used for application deployment on mainframes.
The language was highly specialised for data processing roles and, hence, cannot achieve the general-purpose nature of today’s programming languages. However, it has still kept up with the times, with latest versions of the COBOL language integrating features such as object-oriented programming, input from XML and JSON files, and API access. This is mainly due to the fact that COBOL is heavily entrenched in financial infrastructure and requires updates to keep up with the rest of the tech stack.
While COBOL might be on life support for now, it’s nowhere close to dead. Today, 43% of US banking systems are built on Cobol, with 95% of ATMs relying on COBOL code to keep running. An estimated 80% of in-person transactions also use COBOL, with estimates putting the total amount of COBOL usage at around 220 billion lines of code.
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Banks in the US also post openings for COBOL programmers to this day, mainly aimed at maintaining and modernising their ancient infrastructure. Mainframe manufacturers like IBM and Fujistsu, along with community efforts like GnuCOBOL, have kept the language relevant and supported mainly due to its entrenched nature. Institutions that have adopted this language likely see no sense in upgrading their systems, due to the large amount of resources required to do so.
Due to the large codebases contained within many COBOL-specific mainframes, it is simply a behemoth task to port them to modern languages and is impossible in many cases without shutting down mission-critical operations. Moreover, as COBOL is a domain-specific language, knowledge gained in it cannot be applied in other programming languages. It is likely that this will result in COBOL programming jobs going up in value as older talent erodes away with time.
Fortran: The Speed Demon of Programming
Fortran was first created in 1954 by a team at IBM looking to develop an alternative for assembly languages used in mainframes. Standing for FORmula TRANslator, Fortran was created as an alternative to hand-coding formulas for scientific applications. One of the first documented use cases of Fortran was calculating missile trajectories, later extending to complex physics simulations and mathematical calculations.
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As it was created to be used on early high-performance computing systems, Fortran was built from the ground up to perform calculations quickly. Owing to this, Fortran is one of the fastest programming languages even today, with only compiled languages like C and C++ being able to compete with its speed. This is mainly due to the fact that the language was highly restrictive towards the programmer, allowing the compiler to optimise the code heavily.
Fortran also runs close to metal, implying that it has extremely granular access to the low-level hardware of the system it is running on. Moreover, its killer feature known as ‘multidimensional arrays’ allows it to ingest large amounts of data in many dimensions while still being able to access them at a high speed. This feature, along with the easy syntax of Fortran, lent itself to widespread adoption by the scientific community.
Fortran commonly finds applications in the fields of physics and mathematics. Large scale simulations with millions of data points, like astrophysical modelling, molecular dynamics, fluid dynamics, applied mathematics and weather prediction models, are usually built on Fortran due to its array system and code optimisation. Moreover, Fortran comes in-built with all the required features for scientists, with other languages like C++ requiring multiple non-standardised libraries to enable must-have features.
While COBOL gains its longevity through industry inertia, Fortran instead relies on its blazing fast speed and easy-to-learn syntax to stay relevant. Even today, Fortran is the go-to language to benchmark new supercomputers due to its scalable nature. The language is also maintained to this day, and is in active development. Fortran 2023 is slated for release this year, and representative bodies like the US Fortran standard committee have continued to standardise the language and add new features to it.
The Immortal Languages
These grand old languages are alive and kicking to this day but for two very different reasons. COBOL shows the power of widespread adoption, staying alive through its sheer presence in the financial domain. Fortran, conversely, is striving to keep up with modern programming languages by adding new backwards-compatible features and remains in active development to this day.
Even though modern computing languages are progressing towards a more generalised approach, these capable domain-specific languages have become a mainstay of some of the most important verticals in the age of computing. While no programmer would recommend a novice to learn either of these archaic languages, it is clear that these languages are going nowhere even in the era of exaflop supercomputers.