The English Programming Language
github.com
github.com
MULTIPLY TAX-RATE OF STATE(43) BY BALANCE GIVING SALES-TAX-AMOUNT.
sales_tax_amount = balance * state[42].tax_rate;
(ETA: Added semicolon.)
(ETA2: Fixed critical indexing bug.)
#define MULTIPLY sales_tax_amount = balance * state[43].tax_rate; //Note the semicolon is significant. Barbaric, I know.
So that'd be state[42].
I've put in a PR to upstream. LGTM
It's called ADD 1 TO COBOL GIVING COBOL.
C++
Could I now get you to criticize eating healthy, please? :)
What could go wrong?
I am altering the data. Pray I do not alter it further.From decades of experience, I know intuitively that they are, but I find myself unable to formulate a concise description of what exactly is wrong with this approach.
In fact, given that this is how all the languages that humans are already familiar with work, it's hard to see why this wouldn't be the best approach for constructing a programming language.
- humans can ask back questions to clarify any ambiguity; computers don't have the capacity to understand ambiguity, let alone asking for clarification.
- computers are trusted to work w/o failure almost 100% of the time. humans err (to be human is to err, anyway), so we'd never put a human in charge of critical things we use computers for.
For instance, the poem, or should I say program using the example in the post has several different interpretations, and at least some of those teachers would say are flabbergastingly incorrect.
If you treat them as English you'll get burned. You have to still treat them as very precise formal languages where apparently trivial/irrelevant details are significant, and minor hard-to-spot mistakes will break your program.
Having more explicitly formal/structured syntax makes it easier to distinguish the different parts of the language, make sense of the details, and figure out what is or isn't allowed.
The best description I have for languages like this, e.g. Applescript, is that they are "read only languages" (in the opposite direction old-style Perl has been called a "write only language"): That is, if you have an already written program in hand it will be easier for a complete novice to read (at least, single isolated lines of code will be). But writing new programs is a huge pain in the ass.
In my opinion it’s because of english’s evolution over time. Something that might have made perfect sense in the past becomes an antiquated way of saying the same thing in the future. It also deliberately encodes the authors belief about how language should be spoken ignoring any regional variances you see in the real world.
When you abstract away the English meaning of code into something new and unchanging, you provide stability not seen in natural language.
The first pitfall of using english as a programming language that occurs to me (as a totally Cobol ignorant person):
* Human languages tend to be nebulous around the edges and fluid, often with single word taking up multiple meanings and same function done by multiple words. There are multiple ways to express the same concept. This allows for the language to change and evolve with the times.
* OTOH programming languages need to be specific and exact for the computer to be able to interpret it and ensure it functions as expected across devices and over time.
This means to make English function as a programming language, we will have to take the existing language, whittle down most of the senses and many words, assign one function to one word and use a very trimmed down and reduced version of English.
Now you will have to know two forms of English * The human one * The computer-compatible one
Worse, our human version of the language can often trip up our computer-compatible one. I imagine even debugging would be harder, because when you look into the code, the brain would see perfectly good english and not register any issue with punctuation or tokens as expected by the interpreter.
Consider the below version.
MULTIPLY TAXRATE FROM STATE(43) WITH BALANCE GIVING SALES-TAX-AMOUNT.
I've never used COBOL before, but this thread and your post made me curious and I installed GNU Cobol and found a sample program that demonstrates a few language features.
After playing around with it a little, I think I've understood that "OF" is like a struct element (or object property) accessor, the parens are an array index, and the hyphen is a syntactically significant part of the identifier. "BY" is apparently a mandatory part of the multiplication operator.
Conclusion: each of your three changes (while, as you said, perfectly reasonable from the English language point of view) would indeed break the COBOL code!
By the way, I remember this being a bit of an issue when I tried programming in HyperTalk: on occasion I would unintentionally come up with an English synonym for some natural-language HyperTalk code, and it wouldn't be valid HyperTalk.
LOL!
Though I have a bug report. There are actually only 320k. This makes me feel sad.
Well, there’s Inform 7: https://ganelson.github.io/inform-website/ :)
I found it as you describe, but that was after spending decades with more conventional programming languages. Meanwhile, there are folks over in the IF community who, despite to the best of my knowledge never having written a meaningful amount of what you and I would recognize as code, turn out works of complexity I'd never have imagined you could achieve with Inform 7.
It doesn't have all that much value to me, although I've found it fun to play with, but too many people have done too well with it for me to want to write it off entirely. I think we're just no more for it than it is for us.
although this is one of my favouite programs (or poems), i have never before noticed that it is one quite long poem (or program) terminated by a period - i wonder why Frost did that? possibly a pascal programmer?
Is silicon this implies a large amount of memory and processing capacity, and in carbon the training process takes decades, even though the cost is (amazingly) lower. The big downside of carbon based solutions is that each instance has to be individually trained, so scaling is a serious problem. Not only that, but the success of the training stage is not predictable, and retraining is usually ineffective.
Interestingly, EPL is considered by some to be an exemplary example of the “data as code” paradigm, since the majority of the processing is pre compiled into the n-dimensional memetic matrix.
Even though the mematrix is so massive that resource consumption is high just to move tiny fragments in and out of working memory, it enables the use of simple algorithms to produce surprising inference performance. The main requirement for extracting inference from the dataset is that the extraction algorithm perform statistical prediction of sequential tokens, which is easily accomplished in both silicon and carbon based neural networks.
It is also worth noting that each data output is also code, which is then recursively be added to the mematrix even if the output is an error. This requires careful code hygiene and error checking and correction or inference results can quickly go off the rails.
While less problematic at small sites, where it will be assumed that all instances are of the same "dialect", this commonly causes problems at large sites and for internationalization.
Conflicts between versions and/or dialects may be limited to identifier conflicts ("colour" v "color"), may involve terms not recognized by multiple parties, terms with conflicting meaning ("chaps"), or terms unacceptable to some parties ("toilet" v "bathroom") which break the "conversation".
It kind of worked. The biggest challenge was the limitation of gpt-3 or Codex that I was using at the time and the fact that it didn't always return the exact same result. Although with temperature zero it was somewhat stable.
Wasn't English forked from several other intermediate forks (Anglo-Saxon, Germanic, etc.) going all the way back to Proto-Indo-European? I guess that since none of those carried the name "English" (or its original name "Anglish"), all those beta projects don't count in that timespan, otherwise, it has to be at least twice that age.
In both cases they are an interface between the intent a human wishes to convey and the computer that is to execute that intent.
- an ancient Chinese programming language: https://wy-lang.org/
- I am also building an synth/audio graph inspired music programming language: https://glicol.org/
Using English you can set your chatbots character, personality and purpose.
Will it be a helpful assistant like ChatGPT, or be a digital reincarnation of some historical character? Both can be set up in plan english and the LLM will follow your instructions.
Ever read Finnegans Wake
Idk, it just seems a flat re-interpretation of an obvious concept. Good silliness goes deep, imo.
Looking back, we can see how Machine Code, with its intricate and challenging nature, paved the way for more accessible options. Assembly language then emerged, providing a higher level of abstraction and reducing the complexities of directly working with machine instructions. And of course, C followed suit, offering even greater simplicity and ease of use compared to Assembly.
Imagine a future where programming languages, as we know them today, become akin to CPU instructions – a foundational and low-level primitive. LLMs will revolutionize the way we interact with code, providing a unified interface where the complexities of various languages are distilled into a common representation. The proliferation of individual programming languages will wane. Knowing Java or C++ will become a rare skill, akin to individuals specializing in low-level optimizations using Assembly language these days.
Edit: as time progresses, even the convenience of LLMs may pose challenges, given our inherent tendency towards laziness, so an additional layer of abstraction will be introduced, bridging the gap between LLMs and spoken languages. BCIs will revolutionize the act of coding itself so that individuals can seamlessly "code" by simply "thinking" about their desired actions.