The year 2020 is coming to an end and we can finally relax a bit. In order to lighten up your mood, this blog entry is comprised entirely of humor, satire and plain silliness. Nothing in it has any resemblance with reality and you should not try any of this at work. But if, for whatever reason, you find something useful in here and go to revolutionize the world of software development, remember that we’ve called it first.
There are many programming languages for all sorts of purposes. If you’ve developed software for some decades, you saw them appear, getting useful and being forgotten over the span of time. But what will the future bring? Here are the descriptions of three programming languages that have their purpose, but the world is not ready for them. They aren’t even invented yet!
A programming language for long-lived projects
Most of today’s world source code is categorized as “legacy code”. This degatory term describes code that is old, unwieldy or just too clever for current programmers. Typical programming languages that have lots of legacy code include Cobol, C and Java. Most programmers don’t associate themselves with that code. It’s “other people’s” code. But there is one programming language that not only embraces the notion of “legacy code”, but in fact imposes it. This programming language is “Legacy”, the most productive one to produce heaps and heaps of, well, legacy code in short manners of time.
An unique feature of Legacy is that the code can be written at nearly the speed of thought, but is impossible to decipher even minutes later. A typical Legacy project doesn’t employ version control to differentiate between new and old code, but line numbers: Lower numbers indicate older code, while higher numbers are written more recently. To really drive this point home, every line of code needs to start with its line number, just like the good old BASIC did. An useful convention in Legacy is to choose the line number based on your current timestamp like 20201221181736 (the moment this text got written). Modern Legacy IDEs do this automatically for you.
(A cool but seldom used syntax feature that is based on the timestamp convention is the time-relative jump: You can address your jump target by absolute or relative line number, but even cooler is the relative amount of time: “jump -3d” resumes code execution at the line you wrote three days ago. Just remember: “jump +3d” is equivalent to undefined behaviour for most practical use cases. Only Legacy wizards can pull the “just-in-time jump” off in a useful manner.)
The most pressing issue about Legacy are its third-party dependencies: There are none. All dependencies are second-party dependencies, meaning they are much more involved in your project as usual. In order to compile or deploy a Legacy project, you need to have the exact version, down to the patch and oh-crap-i-forgot-hotfix number, of
- the Legacy SDK
- the compiler
- the IDE
- the Legacy runtime
- and your text encoding
The last point might be surprising, but given the different versions of Unicode and even UTF-8, the Legacy ecosystem has chosen to follow the ideal of Python that dictates the indentation, but redirect it to the parts outlined above. You don’t get to choose the compiler version, the compiler version chooses you, based on your Unicode level. By the way, indentation is a no-brainer in Legacy: Each line starts with the line number, that is enough indentation already.
If you want to deploy a Legacy project to a production server, you need, by the rules above, the exact machine with a perfect replication of all installations for development. Because this is a painful endeavour, most developers have adopted the best practice of “one machine per project” and develop directly on the production server. Most of the time, this is a surprisingly powerful machine, making programming even more faster (remember, the goal is to produce the most amount of code in the least time). It also shortens the delivery pipeline length and facilitates communication between business and development departments, even if not of the pleasant type.
A curiosity that novice Legacy programmers often don’t grok at first is the IMPOSE keyword. It is a variant of the IMPORT functionality of other languages, but doesn’t extend the capabilities of your code. Instead, it limits the ability of the developers in this project by the given imposition. A typical example would be the line
IMPOSE variable name length <= 3
That, as you can read in clear text, limits your variable names to three characters or less. You can often find Legacy code with variable names like “usr” instead of “user”, “pwd” instead of “password” and “idx” instead of “index”. They all follow the imposition above, increase your typing speed and speed up the compilation, which counts as a triple win.
So, if you want to impress your customer with huge amounts of important looking code and build a certain reputation among peers, Legacy might be your new favorite language. And if anybody calls your work result “legacy code” in the future, you should feel validated and proud.
A programming language for mission-critical software
Software written for high-stake contexts like flight control, medical supervision and power plant management needs to meet extreme requirements in regard of correctness, robustness and resilience. Most mainstream programming languages have reacted by providing additional complexity to address the situation. For example, the demand for correct software has lead to the rise of testing frameworks that introduce additional syntax and require additional source code that is, by definition, untested in itself.
This is the problem the inventors of “Untested” try to solve. By writing your code in “Untested”, you can forgo all the extra effort of trying to prove it right. Untested code is, by definition, good enough without test. Remember the definition of Michael Feathers?
To me, legacy code is simply code without tests.
Michael Feathers in his book “Working Effectively with Legacy Code”
If you are ok with “Legacy”, you probably also enjoy “Untested”. The language makes it impossible to write tests for your code, so you can fend off the demand for them more easily. Your boss cannot ask for things that are impossible to do.
One interesting way in which “Untested” wards off calls from test routines is to couple every statement with a side effect in the hardware (oftentimes the TRAP flag on the CPU is flipped). Most programmers in traditional languages find those lines not testable and try to factor them away in order to test the rest. Untested factors away the rest. You don’t need to feel guilty about your lacking test coverage – it’s a feature, not a bug.
If your boss asks if a certain module is thorougly tested, you can respond “yes” in good faith. It’s tested in the best manner possible with “Untested”. If you need to give an overview of your system, you can write “Untested” beside every module and your reviewers will accept it as accurate.
Oh, the problem of long and tedious code reviews are taken into account, too. Because “Untested” code is just “Legacy” code (see Michael Feather’s definition above), it is impossible to read and understand with the exception of the developer machine (aka production server). If a thing is impossible to do, why even start trying? This will give you more time to produce “Untested” code.
And if problems arise in production? Well, you are already on the machine, so you can just hotfix it. Nobody can blame you, you’ve stated again and again that it’s untested code.
By the way: “Hotfix” is another promising programming language worth speaking about, but that would go beyond the scope of this blog entry. Might add it later, though.
A programming language for non-programmers
The central tragedy of software development is that the people that CAN program don’t know what they SHOULD program and the people that know exactly what SHOULD be programmed CANNOT do it. The latter group is mostly managers and people with million-dollar ideas.
The new kid on the programming language block tries to solve this problem by utilizing state-of-the-art artificial intelligence in the compiler AND the runtime. We are talking, of course, about “Straightforward”. It’s a programming language with a natural syntax that’s so easy and lenient, you can call it, well – you probably get the joke by now.
Remember the last time a stunned manager tried to explain the new feature to you and, when you came up with an estimate encompassing weeks for the implementation, shouted out “but it’s straightforward!”. He talked about his preferred programming language and you probably misunderstood him again.
“Straightforward” is so popular with the business folks because the compiler is in the “do what I mean” category of compilers. By using natural language recognition, it infers your most probable meaning of the code, looks it up on the internet and translates it into machine code. The first versions used sites like stackoverflow.com for the translation step, but that didn’t work out, because the site is filled by developers, not business people. Newer versions just access the cloud and find the answer there.
The machine code of “Straightforward” is not actual binary code, but an intermediate representation, much like Java’s bytecode, but for non-technical concepts. Because these concepts are subject of interpretation and the zeitgeist, they are really interpreted again at execution time by another artificial intelligence. This approach might be a bit demanding with processing power, but that’s just a financial problem. The big advantage is that code like “Make the colors more lively!” is both compilable and executable and yields the correct results regarding the current fashion every time. Your color scheme doesn’t age as fast or virtually not at all with this straightforward code.
The only problem that prohibits widespread adoption of “Straightforward” in the business right now is the unsolved equation:
Do what I mean != Do what I want
This is a fundamental theoretical problem in the field of management, much like P = NP in computer science. The race has already started, whoever solves his equation first gets the prize. It is rumored that quantum computing is the key to both. But I suspect that if quantum computing is available for everyday use, other programming languages like “ASAP” will take over the market.
Your turn
I hope this blog post has entertained (and maybe inspired) you. Now, it’s your turn. What is the programming language you always wanted to use? Be silly, be creative, be vocal. Write a comment below and tell us!
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