Have you ever wondered how coding languages came to be? Or why English ended up so dominant across programming? Excellent questions! Join me on a journey across coding history to learn where it all started and where it might go next.
How we arrived at today‘s coding languages
In the early days of computing, programmers worked closest to the machine using strict binary numbers and hexadecimal addresses. This low-level control came at the cost of development speed.
According to expert Maryam Nazari, it could take "weeks to code a few instructions." She explains that as hardware and software advanced, more human-centric languages emerged to accelerate work.
The first wave came in 1950s – assembly languages like COBOL and FORTRAN. Instead of binary, these let programmers use English-like words, symbols and structure. More portable and efficient languages followed, leading to staples like C, C++ and Java.
As Maryam notes, the tradition of favoring English had less to do with culture than convenience:
Early coding education assumed English literacy. Using recognizable vocabulary and grammar lowered the learning curve. And English had grown pervasive in global tech contexts.
With the Web‘s commercialization in the 1990s, scripting languages like JavaScript, Python and PHP became pillars of rapid application development. Their flexible, forgiving syntax enabled anyone to embed coding straight into web pages.
According to data from RedMonk, JavaScript has remained the most popular language for years thanks to its 97% share among websites. Python reaches near 50% by powering prominent web apps and services behind the scenes.
Popular Programming Languages
| Year | Top Languages |
|---|---|
| 1970s | C, Pascal |
| 1980s | C++, Objective-C |
| 1990s | Perl, Python, PHP, Java, JavaScript |
| 2000s | Java, C#, Python, PHP, JavaScript |
| 2010s | Java, C, Python, C++, C#, JavaScript |
As this landscape took shape over decades, English became deeply embedded across tools, resources and code itself. This made it exponentially harder for alternative languages to gain traction.
Can other languages rival English in coding?
In short – yes, but it hasn‘t been easy. Skilled programmers have created languages rooted in their regional dialects rather than English. For example:
- Ruby – An elegant, productive language designed in Japan
- Kotlin – Created by Russian engineers to expand Android development
- Lua – A lightweight scripting language conceived in Brazil
Lua‘s adaptable nature has made it a popular choice for adding scripted logic across games and apps. Kotlin improves programming experience across mobile platforms. And Ruby carries strong global appeal, influencing later languages like Apple‘s Swift.
Still, none have come close to unseating stalwarts like JavaScript or Python. Why? Network effects and compounding tradition.
English took root at pivotal moments like the Web‘s coming of age. Tools and resources coalesced around these languages, creating gravity wells that attract more users, tools and resources. Successfully "re-localizing" coding requires overcoming relentless network momentum.
Consider leading Chinese language Xia. Programmer Tao Wang explains Xia‘s uphill battle:
"Early Xia users struggled without learning resources. Later adopters worried about career options. It‘s hard getting critical mass when existing languages have so much ecosystem advantage."
The same dilemma confronts other regional languages. They must entice new users despite fewer libraries, frameworks and career opportunities. It‘s an enormous challenge.
Transcending languages through math and logic
Spoken languages have nuance. Programming aims for perfect precision. This is why most coding relies heavily on formal logic, mathematics, and universal symbols.
Familiar math operators like +, -, * and / carry identical meaning to all coders regardless of human language. And symbolic logic preserves truth unambiguously across translation. No matter your native tongue, expressions like:
x = y IF a AND b OR NOT c… convey identical meaning. Such reliable universality allows complex ideas to transmit losslessly between regions and cultures.
Visual languages like MIT‘s Scratch further eliminate linguistic dependency. By snapping together logic blocks rather than typing syntax, people of all ages can engage coding free of language barriers.
Looking ahead at global coding potential
As the world grows more interconnected through technology, inclusive coding literacy unlocks opportunities across societies. English support will likely remain essential, but shouldn‘t restrain wider participation.
Striking the ideal balance between localization and interoperability remains an open challenge. But computing history shows progress accelerates when new perspectives join the effort.
The coming decades may reveal global languages we can‘t yet envision. Their emergence could depend profoundly on young innovators everywhere seeing potential through shared symbols, math, logic and imagination transcending linguistic limits.
Our coding journey towards broader access and creativity thus continues…
So in summary:
- Coding began using numbers and evolved English-like structure for accessibility
- Global languages have struggled against mature English ecosystems
- Math and logic enable universal communication in code across cultures
- Computing‘s future will depend on empowering young talent worldwide
Hopefully this gives some useful perspective on coding‘s origins and future possibilities. What other aspects would you like us to explore? Let me know in the comments!
