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I completely disagree with your disagreement. There is plenty of innovation in the programming language space. There is too much. We're too busy working out

I completely disagree with your disagreement. There is plenty of innovation in the programming language space. There is too much. We're too busy working out how to talk to the machines versus how to get problems solved. We're here to solve problems, not serve the machines. In fact, the shortage is in computer-science research. There has been NOTHING as fundamentaly important as Knuth's work in the last couple of decades. It's an innovation standstill. Nothing fundamentally better than the UNIX and LISP paradigms is out there for example. Until something fundamental changes, most of what we have will do the job fine.

llimllib 15y ago
> There has been NOTHING as fundamentaly important as Knuth's work in the last couple of decades. What work of Knuth's? TOACP? TeX? I'm a huge Knuth fan, but I don't see his work as fundamental to computer science, rather mostly as an amazing gatherer and editor of such work.
- pointyhat 15y ago
  He formalised it which is the one thing everyone else had failed before. Plus don't forget things like KMP algo, METAFONT, TeX, literate programming etc.
- pnathan 15y ago
  If I recall correctly, he invented rigorous algorithm analysis in the process of writing TAOCP.
- wazoox 15y ago
  Read this and learn what Knuth did as his summer job in 1960 (he was 21 or 22): http://ed-thelen.org/comp-hist/B5000-AlgolRWaychoff.html#7 http://ed-thelen.org/comp-hist/B5000-AlgolRWaychoff.html#7 here is the conclusion of the chapter: "In 1961, the National ACM meeting was held in Los Angeles. The keynote speaker was Tom Watson, the Chairman of the Board Of IBM. Bob Barton was the second or third speaker after Watson. don and Lloyd and I were in the audience of approximately 1200 people. [...] "There are only three people in this room that really know how to write a compiler and I would like for them to stand up now. They are don knuth, Lloyd Turner and Richard Waychoff."
- xyzzyz 15y ago
  You might be interested in his resume: http://www-cs-faculty.stanford.edu/~uno/vita.pdf http://www-cs-faculty.stanford.edu/~uno/vita.pdf
- psykotic 15y ago
  > I'm a huge Knuth fan, but I don't see his work as fundamental to computer science You're talking about the guy who invented LR parsing.
Rusky 15y ago
Language innovation is tightly tied into computer science innovation. There are plenty of paradigms that are fundamentally different and quite potentially better than UNIX and LISP out there- you just need to get out of that rut. Mozilla's language [Rust](https://www.github.com/graydon/rust/wiki https://www.github.com/graydon/rust/wiki) is working on static verification (using typestate) and concurrency in a C/C++ level language. The Haskell community has several people ([Conal Elliot](http://conal.net http://conal.net), [Luke Palmer](http://lukepalmer.wordpress.com) http://lukepalmer.wordpress.com)) who are working on new models of functional I/O such as functional reactive programming. There is a lot of programming language innovation in parallel/concurrent programming that's just hitting mainstream- actor model, asynchronous programming, CUDA/OpenCL, etc. The way you talk to the machine is an extremely important part of "how to get problems solved." If you can't express something without absurd amounts of overhead, you're not going to solve the problem that way.
- pointyhat 15y ago
  Look at the fragmentation in your comment above. It should start with math and formal verification (top down) rather than with the language (bottom up). Start here: http://www.cs.utexas.edu/users/EWD/ewd10xx/EWD1036.PDF http://www.cs.utexas.edu/users/EWD/ewd10xx/EWD1036.PDF
  - yxhuvud 15y ago
    The reason there is a lot of fragmentation is that there is a lot of different problems out there to solve. There are no pana cea that solves every problem at once. It should start with a problem and then formulating abstractions to make the problem easier to solve. Or in other words with defining a language and then see what properties it has. Starting with the verifications gives you very well defined properties, but it doesn't solve your problems because you will then optimize your language for the wrong thing.
  - Rusky 15y ago
    I'm not sure what you're saying. Do you honestly expect every PL researcher to all work on the same magical super-language? No- they're going to work on the problem in their area of expertise and create/modify a language to show off their ideas. Then a language like Scala or Haskell or Clojure can come along and improve on them or combine them. Every field works this way. That's why there is more than one particle collider, more than one drug for each problem, more than one theory of particle physics, more than one programming language. Your link talks about radical change over gradual change in computer science. It seems to support the idea of creating new and dramatically programming languages. The idea that "small" changes have large effects discourages the gradual modification of existing paradigms and languages.
pnathan 15y ago
Agreed. Right now the only significant research breakthrough I've seen is the work on formal analysis of programs. I have read hundreds of computer science papers from the 60s, 70s and 80s as part of my academic work, and frankly, everything I'm seeing today was conceptualized and/or invented then. It's staggeringly obvious if you read the sweep of history as written by journal article titles in, say, Software Practice & Experience, between 1970 and 2010. Somewhere in the late 80s things just peter out. I strongly suspect a few things have come into play here. * Disdain for formal mathematics by software writers. Mathematics is so absolutely key to heavy-duty breakthroughs in computer science. * Increasing percentages of academics who never worked in the real world (and consequently knew how to get stuff done or what really matters). * Lack of the academic industrial research labs such (Hi MS Labs! You are awesome! Keep it up please!). Also, lack of massive DARPA/DoD/DoE & NASA funding. * The general decline of academic research quality, sacrificed on the altar of metrics (e.g., papers per year) & budget cuts. * Friction caused by standards and legacy data & code. It's easy to innovate in a greenfield world. When you have to support five gazillion things & have 'batteries included', barriers to adoption are a lot higher. I suspect major seminal work in the next decade will come from the Haskell crowd, since they are the most mathematics-heavy writers, and it is gaining traction in Microsoft and Google, which have the budget to support offbeat research.
- deleted 15y ago
  [deleted]
- pointyhat 15y ago
  Thank you - this is my entire line of thought.
- beambot 15y ago
  So... you're given a blank check, either as a industrial research lab manager or DARPA program manager. What "revolutionary" research in CS would you champion? It's easy to be critical from the sidelines. There are very smart people still working in this space, including Knuth himself.
  - pnathan 15y ago
kunley 15y ago
I disagree with your disagreement of the original disagreement. Plenty of languages does not mean plenty of innovation; in the web programming there's certainly too less of it. Every new or currently fashioned language evolves to a point where community implements its own Rails in it. I hope you don't call this trend innovation because it's not. There were some promising trends in web programming like use of delimited continuations, but they didn't make a breakthrough. Today's web dev still is a hack around stateless http protocol, requires you to know at least 3 languages and there are no composable components you could easily reuse. World definitely needs innovation in this area.
- Rusky 15y ago
  Definitely agree. Mainstream language design seems to be stuck on endless variations of Ruby, JavaScript, and Java. I would love to see as many new languages as we have now, but focused on more significant changes than "Lisp without macros and a slightly tweaked generics system."
  - hbbio 15y ago
    You should really check Opa, which has been discussed several times here. The syntax does not please everyone (and can evolve) but at least it is built on original concepts. See http://opalang.org http://opalang.org. An alternative is Ur/Web if you're that curious.
- wnight 15y ago
  Like AI, if you define innovation as something large enough then we'll never get there. I think there's a lot in the small steps. It's only by implementing a framework ten times that it'll be done really well. In one language you'd never get traction for the later frameworks. If each community does one with knowledge of the ones before them eventually a great implementation will be created.
0x12 15y ago
> In fact, the shortage is in computer-science research. and > There is plenty of innovation in the programming language space. Are at odds with each other. All of the programming languages that we use today can trace their roots back to computer-science research, either in the dark ages or in the immediate past. Things like software transactional memory and other goodies are the pay-offs from that research and those things are only now making their way into programming languages. You can't have the one without the other. And that goes both ways, computer-science research needs to have people that try the concepts it comes up with in the marketplace to see what survives in an adversarial context, so that it will be able to make the next step based on what survived and what didn't. So that's two birds with one stone, it's a proving ground and the foundation for the next generation of concepts.
- pointyhat 15y ago
  Computer science != programming language. Computer science is at a far lower level of abstraction than meta-languages and compilers.
  - scott_s 15y ago
    Most people I know consider programming languages and compilers a part of computer science. This set of people is mostly computer science researchers, some of whom (including myself) who do work in the area.
    - pointyhat 15y ago
      That's at a very high level. It's part of, but it's not the driving force behind what is possible. That is the constraints of the universe and consequentially mathematics, on which there is little focus these days. Programming languages and compilers are the easy part of the problem. Translation is almost completely solved. However, the abstractions over the top at both the conceptual and structural level (logic->machine) are definitely not solved.
      - scott_s 15y ago
zobzu 15y ago
plan9 singularity both, similar in some concepts, just kills UNIX on the design stand point. None of them are really used. Sad :( Eventually we will merge toward them tho, they're the future somehow. Not because they're "new" (compared to UNIX) but because they solve resource and security issues we have today. Also solves a lot of the complexity.
- MatthewPhillips 15y ago
  Unix survives because it's good enough. A successor doesn't have to beat it; it has to blow it away. [1] http://www.faqs.org/docs/artu/plan9.html http://www.faqs.org/docs/artu/plan9.html
naasking 15y ago
Completely disagreed. There is a lot of language creation, but little language innovation. Ruby, Python, Perl, Lua, JavaScript are essentially all the same language. Java and C# are the same, and very similar to the scripting languages just adding static typing. C++ is similar to the previous 2, just removing memory safety. What was so innovative about any of these languages? They are the same old imperative OO paradigm that first appeared in Simula and Ada back in the 80s. Examples of languages that are innovative are Mozart/Oz, Haskell, Alice ML, Coq, Agda and Mercury. These completely redefine what it means to program, and all of them were created in the last 15-20 years. And if you think there haven't been great strides in each of these domains, then you're simply not familiar with them.
apotheon 15y ago
> There is plenty of innovation in the programming language space. There is too much. No such thing. Innovation is a good thing, period. Perhaps what you find objectionable is the proliferation of stuff that people call "innovation", but really isn't very innovative.

llimllib 15y ago

> There has been NOTHING as fundamentaly important as Knuth's work in the last couple of decades. What work of Knuth's? TOACP? TeX? I'm a huge Knuth fan, but I don't see his work as fundamental to computer science, rather mostly as an amazing gatherer and editor of such work.

pointyhat 15y ago
He formalised it which is the one thing everyone else had failed before. Plus don't forget things like KMP algo, METAFONT, TeX, literate programming etc.
pnathan 15y ago
If I recall correctly, he invented rigorous algorithm analysis in the process of writing TAOCP.
wazoox 15y ago
Read this and learn what Knuth did as his summer job in 1960 (he was 21 or 22): http://ed-thelen.org/comp-hist/B5000-AlgolRWaychoff.html#7 http://ed-thelen.org/comp-hist/B5000-AlgolRWaychoff.html#7 here is the conclusion of the chapter: "In 1961, the National ACM meeting was held in Los Angeles. The keynote speaker was Tom Watson, the Chairman of the Board Of IBM. Bob Barton was the second or third speaker after Watson. don and Lloyd and I were in the audience of approximately 1200 people. [...] "There are only three people in this room that really know how to write a compiler and I would like for them to stand up now. They are don knuth, Lloyd Turner and Richard Waychoff."
xyzzyz 15y ago
You might be interested in his resume: http://www-cs-faculty.stanford.edu/~uno/vita.pdf http://www-cs-faculty.stanford.edu/~uno/vita.pdf
psykotic 15y ago
> I'm a huge Knuth fan, but I don't see his work as fundamental to computer science You're talking about the guy who invented LR parsing.

Rusky 15y ago

Language innovation is tightly tied into computer science innovation. There are plenty of paradigms that are fundamentally different and quite potentially better than UNIX and LISP out there- you just need to get out of that rut. Mozilla's language [Rust](https://www.github.com/graydon/rust/wiki https://www.github.com/graydon/rust/wiki) is working on static verification (using typestate) and concurrency in a C/C++ level language. The Haskell community has several people ([Conal Elliot](http://conal.net http://conal.net), [Luke Palmer](http://lukepalmer.wordpress.com) http://lukepalmer.wordpress.com)) who are working on new models of functional I/O such as functional reactive programming. There is a lot of programming language innovation in parallel/concurrent programming that's just hitting mainstream- actor model, asynchronous programming, CUDA/OpenCL, etc. The way you talk to the machine is an extremely important part of "how to get problems solved." If you can't express something without absurd amounts of overhead, you're not going to solve the problem that way.

pointyhat 15y ago
Look at the fragmentation in your comment above. It should start with math and formal verification (top down) rather than with the language (bottom up). Start here: http://www.cs.utexas.edu/users/EWD/ewd10xx/EWD1036.PDF http://www.cs.utexas.edu/users/EWD/ewd10xx/EWD1036.PDF
- yxhuvud 15y ago
  The reason there is a lot of fragmentation is that there is a lot of different problems out there to solve. There are no pana cea that solves every problem at once. It should start with a problem and then formulating abstractions to make the problem easier to solve. Or in other words with defining a language and then see what properties it has. Starting with the verifications gives you very well defined properties, but it doesn't solve your problems because you will then optimize your language for the wrong thing.
- Rusky 15y ago
  I'm not sure what you're saying. Do you honestly expect every PL researcher to all work on the same magical super-language? No- they're going to work on the problem in their area of expertise and create/modify a language to show off their ideas. Then a language like Scala or Haskell or Clojure can come along and improve on them or combine them. Every field works this way. That's why there is more than one particle collider, more than one drug for each problem, more than one theory of particle physics, more than one programming language. Your link talks about radical change over gradual change in computer science. It seems to support the idea of creating new and dramatically programming languages. The idea that "small" changes have large effects discourages the gradual modification of existing paradigms and languages.

pnathan 15y ago

Agreed. Right now the only significant research breakthrough I've seen is the work on formal analysis of programs. I have read hundreds of computer science papers from the 60s, 70s and 80s as part of my academic work, and frankly, everything I'm seeing today was conceptualized and/or invented then. It's staggeringly obvious if you read the sweep of history as written by journal article titles in, say, Software Practice & Experience, between 1970 and 2010. Somewhere in the late 80s things just peter out. I strongly suspect a few things have come into play here. * Disdain for formal mathematics by software writers. Mathematics is so absolutely key to heavy-duty breakthroughs in computer science. * Increasing percentages of academics who never worked in the real world (and consequently knew how to get stuff done or what really matters). * Lack of the academic industrial research labs such (Hi MS Labs! You are awesome! Keep it up please!). Also, lack of massive DARPA/DoD/DoE & NASA funding. * The general decline of academic research quality, sacrificed on the altar of metrics (e.g., papers per year) & budget cuts. * Friction caused by standards and legacy data & code. It's easy to innovate in a greenfield world. When you have to support five gazillion things & have 'batteries included', barriers to adoption are a lot higher. I suspect major seminal work in the next decade will come from the Haskell crowd, since they are the most mathematics-heavy writers, and it is gaining traction in Microsoft and Google, which have the budget to support offbeat research.

deleted 15y ago
[deleted]
pointyhat 15y ago
Thank you - this is my entire line of thought.
beambot 15y ago
So... you're given a blank check, either as a industrial research lab manager or DARPA program manager. What "revolutionary" research in CS would you champion? It's easy to be critical from the sidelines. There are very smart people still working in this space, including Knuth himself.
- pnathan 15y ago

kunley 15y ago

I disagree with your disagreement of the original disagreement. Plenty of languages does not mean plenty of innovation; in the web programming there's certainly too less of it. Every new or currently fashioned language evolves to a point where community implements its own Rails in it. I hope you don't call this trend innovation because it's not. There were some promising trends in web programming like use of delimited continuations, but they didn't make a breakthrough. Today's web dev still is a hack around stateless http protocol, requires you to know at least 3 languages and there are no composable components you could easily reuse. World definitely needs innovation in this area.

Rusky 15y ago
Definitely agree. Mainstream language design seems to be stuck on endless variations of Ruby, JavaScript, and Java. I would love to see as many new languages as we have now, but focused on more significant changes than "Lisp without macros and a slightly tweaked generics system."
- hbbio 15y ago
  You should really check Opa, which has been discussed several times here. The syntax does not please everyone (and can evolve) but at least it is built on original concepts. See http://opalang.org http://opalang.org. An alternative is Ur/Web if you're that curious.
wnight 15y ago
Like AI, if you define innovation as something large enough then we'll never get there. I think there's a lot in the small steps. It's only by implementing a framework ten times that it'll be done really well. In one language you'd never get traction for the later frameworks. If each community does one with knowledge of the ones before them eventually a great implementation will be created.

0x12 15y ago

> In fact, the shortage is in computer-science research. and > There is plenty of innovation in the programming language space. Are at odds with each other. All of the programming languages that we use today can trace their roots back to computer-science research, either in the dark ages or in the immediate past. Things like software transactional memory and other goodies are the pay-offs from that research and those things are only now making their way into programming languages. You can't have the one without the other. And that goes both ways, computer-science research needs to have people that try the concepts it comes up with in the marketplace to see what survives in an adversarial context, so that it will be able to make the next step based on what survived and what didn't. So that's two birds with one stone, it's a proving ground and the foundation for the next generation of concepts.

pointyhat 15y ago
Computer science != programming language. Computer science is at a far lower level of abstraction than meta-languages and compilers.
- scott_s 15y ago
  Most people I know consider programming languages and compilers a part of computer science. This set of people is mostly computer science researchers, some of whom (including myself) who do work in the area.
  - pointyhat 15y ago
    That's at a very high level. It's part of, but it's not the driving force behind what is possible. That is the constraints of the universe and consequentially mathematics, on which there is little focus these days. Programming languages and compilers are the easy part of the problem. Translation is almost completely solved. However, the abstractions over the top at both the conceptual and structural level (logic->machine) are definitely not solved.
    - scott_s 15y ago

zobzu 15y ago

plan9 singularity both, similar in some concepts, just kills UNIX on the design stand point. None of them are really used. Sad :( Eventually we will merge toward them tho, they're the future somehow. Not because they're "new" (compared to UNIX) but because they solve resource and security issues we have today. Also solves a lot of the complexity.

MatthewPhillips 15y ago
Unix survives because it's good enough. A successor doesn't have to beat it; it has to blow it away. [1] http://www.faqs.org/docs/artu/plan9.html http://www.faqs.org/docs/artu/plan9.html

naasking 15y ago

Completely disagreed. There is a lot of language creation, but little language innovation. Ruby, Python, Perl, Lua, JavaScript are essentially all the same language. Java and C# are the same, and very similar to the scripting languages just adding static typing. C++ is similar to the previous 2, just removing memory safety. What was so innovative about any of these languages? They are the same old imperative OO paradigm that first appeared in Simula and Ada back in the 80s. Examples of languages that are innovative are Mozart/Oz, Haskell, Alice ML, Coq, Agda and Mercury. These completely redefine what it means to program, and all of them were created in the last 15-20 years. And if you think there haven't been great strides in each of these domains, then you're simply not familiar with them.

apotheon 15y ago

> There is plenty of innovation in the programming language space. There is too much. No such thing. Innovation is a good thing, period. Perhaps what you find objectionable is the proliferation of stuff that people call "innovation", but really isn't very innovative.