Throughout the history of engineering, developers have tried to abstract machine code into something humans can easily understand. No-code finally offers the ultimate abstraction so that anyone can be an engineer.
Imagine you’re a consumer looking to open a bank account. If you’re lucky, you might choose a bank that allows you to submit an application via a mobile or web application. As you fill this out, you probably aren’t thinking much about what happens behind the scenes for enterprises to create this application and deliver it to you. But if you do, most of the time you probably think of code. So what is code really, and how has it developed over the years?
The Concept of Code
If we consider coding conceptually, the overall goal is simply to transform an idea or action into something that a machine can read. While the concept is simple, the reality involves learning a complex syntax in order to effectively speak to a computer.
Even as coding becomes more and more important, the startling truth is that very few people can actually read and write in languages that machines understand. An estimated 4 million people in the United States can code — compared to more than 132 million people in the workforce. This means that only about 3% of the working population can translate their own ideas into applications — a reality that excludes workers with valuable insight from fully participating in the process.
Over time, computer engineers have compensated for the complexity of machine language by abstracting code and moving it closer to natural language. By doing so, they’ve gradually made it possible to simplify the software development process with programming languages that better bridge the gap between machine language and human language.
But in order to fully understand the coding bottleneck, it helps to trace the development and abstraction of programming languages over the years. From early machine code to high-level programming languages, computer engineers have always looked for ways to improve the way we build software. Eventually, this timeline brings us to the emergence of no-code, which offers the ultimate abstraction of machine language — and completely redefines what it means to be an engineer.
Schedule a personalized virtual no-code demo with one of our industry experts.
The Era of Machine Code
Machine code is the native language of computers and requires no transformation for a machine to understand. The concept of binary (0s and 1s), on which machine code is based, was developed by Gottfried Leibniz in the late 17th century. Programming in machine code would require humans to memorize numerical codes and complex modifications just to interact with computers. As a result, almost no one programs directly in machine code.
The Era of Low-Level Programming Languages
Low-level programming languages — also known as assembly languages — provide an initial level of abstraction from machine code. These languages use alphanumeric mnemonic codes rather than binary to provide computers with comprehensible instructions.
In order to make assembly language understandable for computers, however, engineers needed to develop computer programs that translate assembly languages into machine code. These assemblers were initially written in the 1950s and 1960s for computers like the TX-0 and PDP-1, providing a fast way to mediate between machine code and shorter descriptive words more easily read by humans.
The Era of High-Level Programming Languages
First Generation High-Level Programming Languages
The next step in the evolution of coding was toward high-level programming languages. With FORTRAN in 1957 and COBOL in 1959, computer engineers took another step closer to programming in a way that humans talk, using more natural language elements. The first generation of these languages used compilers to translate back into machine code, which came with a performance penalty of its own. However, these languages allowed more people to learn how to program, inspiring the first wave of large-scale academic interest in coding.
Second Generation High-Level Programming Languages
With C++ in 1983, Python in 1991, and Ruby in 1993, the second generation of high-level programming languages streamlined the coding process even further. Developers realized that there were repeatable actions in previous programming languages that could — and should — be automated. By doing so, they made it possible to speed up and simplify the overall coding process compared with the first generation of high-level programming languages.
Frameworks used preexisting high-level programming languages as their core foundation, but then implemented so-called guardrails to increase efficiency. An example of this is Ruby on Rails, developed in 2005. Frameworks such as Ruby on Rails excel in specific use cases, such as web application development, although programmers give up the flexibility of other high-level programming languages for the added efficiency in a limited area of work.
While high-level programming languages represent a major step forward from machine code and their low-level counterparts, they still represent a time-consuming process for developers. Recently, low-code platforms emerged to help further automate development, providing a visual interface for configuration that spits out programming languages for users. From there, engineers edit and improve the resulting codebase where necessary.
The disadvantage of low-code platforms is that they’re still technically using code — meaning that the task of application development continues to be restricted to a small percentage of the population. This also means that much like its predecessors, there are associated legacy costs with low-code — maintenance still needs to be done by classically trained engineers who know how to code.
The Era of No-Code
Finally, no-code offers an entirely new way forward. By fully abstracting code into a completely visual interface, users can rely on components to build applications. This final layer of translation between machine code and human development means that anyone with valuable (and potentially game-changing) ideas can try their hand at building software.
Ultimately, no-code is the true kind of abstraction we’ve been waiting to arrive at all along. No-code allows us to work in natural human languages to create the applications that the modern world demands, all in a faster and more cost-effective way than ever before. By investing in no-code and letting these platforms translate ideas into code for us, anyone can become a programmer.