Much more interesting is the original article, instead of six weak paragraphs.
Wired doesn’t seem to me to be a good source for articles anymore, since they’ve lately just taken to Gizmodo/buzzfeed style rehashing of content better covered elsewhere.
Computer science clocksteps at the rate of algorithms and discoveries. Languages are always going to come and go, unless the language springs up from a good theory.
If you want to understand why this would be true, just look at the history of mathematics. Read about algebraic representations, which kind of abacuses have been used, slide rules, mechanical calculators. You will find out that what we have present today is a small fragment of what used to be, and the stuff that still exists was lugged to today because there’s not many obvious better ways to do the same thing.
By this basis, I’d propose that the current “top 20” by Redmonk cannot form any kind of a long-running status quo. It’s a large list of programming languages rooting to the same theory (Javascript, Java, Python, PHP, C#, C++, Ruby, C, Objective-C, Swift, Scala, Go, TypeScript, Perl, Lua).
There is going to be only one in 30 years, and I think it’ll be falling to C or Javascript axis. They are syntactically near and lot of software was and gets written with these languages. Although there is even more written with C++, it’s way too contrived to survive without reducing back to something like C.
CSS may have some chance of surviving, but it’s pretty much different from the rest. About Haskell I’m not sure. I think typed lambda calculus appear or will reappear in a better format elsewhere. The language will be similar to Haskell though, and may bear the same name.
Unix shell and its commands will probably survive, while Powershell and DOS will wither. Windows seems to have its days counted already by now. Sadly it was not because of open source movement. Microsoft again just botched themselves up.
R seems like a write-and-forget language. But it roots to Iverson’s notation.. Though perhaps the notation itself will be around, but not the current instances of it.
I think that hardware getting more concurrent and diverging from linear execution model will do permanent shakeup on this list in a short term. The plethora of programming languages that describe a rigid evaluation strategy will simply not survive. Though I have bit of bias to think this way so I may not be a reliable source for checking into the future.
But I think this be better than looking at programming language rankings.
I think, most importantly, we haven’t even seen anything like the one language to rule them all. I expect that language to be in the direction of Conal Elliott’s work compiling to categories.
A language that is built around category theory from the start, like you have many different syntactic constructs and the ones you use in a given expression determines the properties of the category that the expression lives in. Such a language could locally have the properties of all the current languages and could provide optimal interoperation.
BTW, I think we won’t be calling the ultimate language a “programming language” because it’ll be as good for describing electrical circuits, mechanical designs and biological systems as for describing programs. So I guess it’ll be called something like a specification language.
“we haven’t even seen anything like the one language to rule them all. “
That’s exactly what the LISPers always said they had. Their language could be extended to do anything. New paradigms and styles were regularly backported to it as libraries. It’s also used for hardware development and verification (ACL2).
Well, it’s hard to say anything about LISPs in general since the span is so vast and academic, and especially for me, since my contact with any LISP is quite limited. But, from my understanding of the common usage of LISP, it doesn’t qualify.
First of all, I think dropping static analysis is cheating, but I don’t intend to tap into an eternal flame war here. What I mean when I say “the properties of the current languages” is no implicit allocations, borrow-checking and inline assembly like in Rust, purity and parametricity like in Haskell, capabilities-security like in Pony etc. etc. , and not only the semantics of these, but also compilers taking advantage of these semantics to provide static assistance and optimizations (like using the stack instead of the heap, laziness & strictness analysis etc.).
And I’m also not just talking about being able to embed these into a given language; you should also be able to write code such that if it’s simple enough, it should be usable in many of them. For instance, it’d be hard to come up with some language semantics in which the identity function cannot be defined, so the identifier id x = x should be usable under any local semantics (after all every category needs to have identity morphisms). You should also be able to write code that interfaces between these local semantics without leaving the language and the static analysis.
I know you can embed these things in LISP, expose enough structure from your LISP code to perform static analysis, get LISP to emit x86 assembly etc. etc. But, IMHO, this doesn’t make LISP the language I’m talking about. It makes it a substrate to build that language on.
I think one major difference between math and computer science, and why we’re not going to see a lot of consolidation for a while (not even in 30 years, I don’t think), is that code that’s on the internet has a way of sticking around, since it’s doing more than just sitting in research papers, or providing a tool for a single person.
I doubt we’ll see 100% consolidation any time soon, if for no reason than that it’s too easy to create a new programming language for that to be the case.
Hardware changes might shake up this list, but I think it’ll take 30 years for that to be realized, but there will be a lot of programming languages that fall out of that.
We’re definitely still going to have COBOL in 30 years, and Java, and C. The rest, I’m unsure of, but I’ll bet that we’ll be able to recognize the lineage of a lot of the top 30 when we look in 30 years.
But the firm’s latest rankings, released last week, show Swift dropping to 11th place. Kotlin slipped from 27th place to 28th place. Though notable, slipping one place in one quarter doesn’t mean that Swift and Kotlin are in decline or even that they’ve peaked. “In general, we caution readers not to assign too much weight to small changes in the rankings; the differences between one spot or another, in general, tend to be slight,” RedMonk co-founder Stephen O’Grady wrote in a blog post analyzing the findings.
They literally quote someone who says that articles like this don’t mean anything…
Much more interesting is the original article, instead of six weak paragraphs.
Wired doesn’t seem to me to be a good source for articles anymore, since they’ve lately just taken to Gizmodo/buzzfeed style rehashing of content better covered elsewhere.
Computer science clocksteps at the rate of algorithms and discoveries. Languages are always going to come and go, unless the language springs up from a good theory.
If you want to understand why this would be true, just look at the history of mathematics. Read about algebraic representations, which kind of abacuses have been used, slide rules, mechanical calculators. You will find out that what we have present today is a small fragment of what used to be, and the stuff that still exists was lugged to today because there’s not many obvious better ways to do the same thing.
By this basis, I’d propose that the current “top 20” by Redmonk cannot form any kind of a long-running status quo. It’s a large list of programming languages rooting to the same theory (Javascript, Java, Python, PHP, C#, C++, Ruby, C, Objective-C, Swift, Scala, Go, TypeScript, Perl, Lua).
There is going to be only one in 30 years, and I think it’ll be falling to C or Javascript axis. They are syntactically near and lot of software was and gets written with these languages. Although there is even more written with C++, it’s way too contrived to survive without reducing back to something like C.
CSS may have some chance of surviving, but it’s pretty much different from the rest. About Haskell I’m not sure. I think typed lambda calculus appear or will reappear in a better format elsewhere. The language will be similar to Haskell though, and may bear the same name.
Unix shell and its commands will probably survive, while Powershell and DOS will wither. Windows seems to have its days counted already by now. Sadly it was not because of open source movement. Microsoft again just botched themselves up.
R seems like a write-and-forget language. But it roots to Iverson’s notation.. Though perhaps the notation itself will be around, but not the current instances of it.
I think that hardware getting more concurrent and diverging from linear execution model will do permanent shakeup on this list in a short term. The plethora of programming languages that describe a rigid evaluation strategy will simply not survive. Though I have bit of bias to think this way so I may not be a reliable source for checking into the future.
But I think this be better than looking at programming language rankings.
I think, most importantly, we haven’t even seen anything like the one language to rule them all. I expect that language to be in the direction of Conal Elliott’s work compiling to categories.
A language that is built around category theory from the start, like you have many different syntactic constructs and the ones you use in a given expression determines the properties of the category that the expression lives in. Such a language could locally have the properties of all the current languages and could provide optimal interoperation.
BTW, I think we won’t be calling the ultimate language a “programming language” because it’ll be as good for describing electrical circuits, mechanical designs and biological systems as for describing programs. So I guess it’ll be called something like a specification language.
“we haven’t even seen anything like the one language to rule them all. “
That’s exactly what the LISPers always said they had. Their language could be extended to do anything. New paradigms and styles were regularly backported to it as libraries. It’s also used for hardware development and verification (ACL2).
Well, it’s hard to say anything about LISPs in general since the span is so vast and academic, and especially for me, since my contact with any LISP is quite limited. But, from my understanding of the common usage of LISP, it doesn’t qualify.
First of all, I think dropping static analysis is cheating, but I don’t intend to tap into an eternal flame war here. What I mean when I say “the properties of the current languages” is no implicit allocations, borrow-checking and inline assembly like in Rust, purity and parametricity like in Haskell, capabilities-security like in Pony etc. etc. , and not only the semantics of these, but also compilers taking advantage of these semantics to provide static assistance and optimizations (like using the stack instead of the heap, laziness & strictness analysis etc.).
And I’m also not just talking about being able to embed these into a given language; you should also be able to write code such that if it’s simple enough, it should be usable in many of them. For instance, it’d be hard to come up with some language semantics in which the identity function cannot be defined, so the identifier
id x = xshould be usable under any local semantics (after all every category needs to have identity morphisms). You should also be able to write code that interfaces between these local semantics without leaving the language and the static analysis.I know you can embed these things in LISP, expose enough structure from your LISP code to perform static analysis, get LISP to emit x86 assembly etc. etc. But, IMHO, this doesn’t make LISP the language I’m talking about. It makes it a substrate to build that language on.
I think one major difference between math and computer science, and why we’re not going to see a lot of consolidation for a while (not even in 30 years, I don’t think), is that code that’s on the internet has a way of sticking around, since it’s doing more than just sitting in research papers, or providing a tool for a single person.
I doubt we’ll see 100% consolidation any time soon, if for no reason than that it’s too easy to create a new programming language for that to be the case.
Hardware changes might shake up this list, but I think it’ll take 30 years for that to be realized, but there will be a lot of programming languages that fall out of that.
We’re definitely still going to have COBOL in 30 years, and Java, and C. The rest, I’m unsure of, but I’ll bet that we’ll be able to recognize the lineage of a lot of the top 30 when we look in 30 years.
Did you mean to write J or APL? I understand R as the statistics language.
They literally quote someone who says that articles like this don’t mean anything…