6 ms·

Anders Hejlsberg Is Right: You Cannot Maintain Large Programs In JavaScript

23 points by gspyrou 14y ago

willvarfar 14y ago
"I haven’t listened to the interview so I honestly don’t know if the quote is taken out of context or not" WTF? -1 for not trying. There's a panel discussion with: Erik Meijer (misc, head of Cloud Programmability Team at Microsoft) Gilad Bracha (Dart) Martin Odersky (most recently Scala) Anders Hejlsberg (Turbo Pascal, Delphi, C# etc) Peter Alvaro (researcher e.g. datalog) And some ungooglable twerp doesn't actually listen to it? Argument from authority seems spot-on when you're replying to something they said. Make that -2
- roopeshv 14y ago
  in all fairness, that sentence is said more like a passing comment and not a discussion topic
  - willvarfar 14y ago
    I posted the original to reddit/r/javascript so I've got a point to defend ;) In the video, they do talk about tooling, IDEs, auto-completion, libraries, dynamic types, and so on. Refactoring tools come up repeatedly. So you can build up a richer context to the reasoning. There's even discussion about reasoning about systems made from components running on different machines, which is not far from what this Derek chap responds with as his perceived solution. Its not all tightly packed into a sound-bite.
dllthomas 14y ago
Certainly, large programs are harder to maintain than small programs. Certainly, modularity and encapsulation helps, in any language. The implication that, therefore, choice of language is irrelevant to maintainability is spurious.
- roopeshv 14y ago
  did you listen to the talk
- vlisivka 14y ago
  Definition of large program is "program, which is hard to maintain". So large programs are hard to maintain by definition.
  - dllthomas 14y ago
    You're referring to a line I never drew. Programs can be larger or smaller in many dimensions - LoC, complexity, features... Other things being equal, the smaller program is easier to deal with. We don't need to say "these programs are large and these are small" to make valid inferences in this area.
bad_user 14y ago
Link-bait. The problem of composability has been debated to death and is in general recognized to be the biggest problem of our software industry. Even Unix-derived operating systems come these days with pretty big and monolithic pieces of software. Even Emacs is technically a big and monolithic piece of software, at least when compared to Vi. But Derick, You Write Large JavaScript Apps ... I write JavaScript applications that appear to be large. Not trying to make an argument about who Derick is, but he's arguing against Anders Hejlsberg, a very talented software engineer and language designer. Certainly we should be wary about appeals to authority (just like the one I've made), however let's not get ahead of ourselves and forget the shoulders of the giants on which we stand.
DanielRibeiro 14y ago
The original talk: http://css.dzone.com/articles/you-can-write-large-programs http://css.dzone.com/articles/you-can-write-large-programs Martin Odersky keeps a sober view on all of this. His insights on sound/unsound type systems is really good. Also, Peter Alvaro makes a very good complaint about having a distinction of library creators and every-day programmers, which the others seem to believe not only to be true, but also to be inevitable (I obviously side with Peter on this). The conversation is much better than this sad remark.
mickeyp 14y ago
I've had this discussion with co-workers before about scripting languages, and in particular Python, as that is what I am working with currently. I feel that once Python -- or indeed any loosey-goosey language that lack strong types -- programs grow beyond a certain size you easily fall into the "inconsistency trap", especially if you have many programmers working on the same code base. You have to be extra diligent with docstrings; unit tests and variable naming, or invent your own poor, ad hoc type checking with isinstance, or liberal use of exception handling if you insist on ensuring that Python's duck typing continues to work in your program. Invariably you'll end up with two camps: those who feel <dynamic lang> scales to large codebases, and those who do not; those in the former camp have (almost never) had to maintain a millions of lines of code before so they do not know just how helpful having a strict compiler is, and just how hard it is to refactor or infer the meaning of code due to the dynamic nature of the language. Linting will only get you so far. It's perfectly possible to write maintainable, large programs in dynamic languages, but it is infinitely harder than it should be.
- reycharles 14y ago
  Python is actually strongly typed. For example, 1+"1" will fail in python. Type errors will (usually) make the program crash. I believe this is a major plus over javascript when writing and maintaining large programs.
  - mickeyp 14y ago
    Yes, crash at runtime. That's no good in a production environment when you can have hundreds of code paths and no real way of ensuring they are all correct. Mistakes happen, and code coverage tools are in my experience pretty useless at ensuring all code paths have been exercised (a theoretically futile task as well.) As for strongly typed- yes, that is true, but it is also dynamically typed, and combined with duck typing you're left with a philosophy that encourages interchangeable types provided the interface is similar. Strong typing come in many forms, and you can have strong types and still have a compiler there to help you out. But of course, no system is perfect. That's all well and good when you still have a complete, mental overview of the code and how it interacts at a macroscopic level. That's much harder to do when you go from 1 to many developers -- especially if you're developing code to be consumed by other developers.
willvarfar 14y ago
I struggle to maintain a large system in Python (which, at least, is strongly typed). My major banes are: * performance. You have a hard job retrofitting performance to Python * typos. Typos that survive my Integration Tests which can never have enough coverage. Stuff that just won't compile in a static language becomes a runtime issue on a dynamic language, and they can hide for months outside the happy path e.g. in some error handing code * poor libraries. I get nice warm happy feelings about various async server frameworks that last until I have to debug them and stare at their innards and realised they were contributed to and diluted by twits * pip/virtualenv doing a poor job with native code in modules At least it has namespaces / modules and such At least its not common for every 3rd party lib to want to squat on a function called $ And so on. Static typing is a major plus when you are beyond the prototyping stage and heading heading towards the release and maintenance phase. Which is why I'm on the look out for implicitly strongly statically typed languages that look like Python :)
- mixmastamyk 14y ago
  Try pyflakes, pylint, etc. They've helped me find a few typos in exception handlers that are rarely run.

23 points by gspyrou 14y ago

"I haven’t listened to the interview so I honestly don’t know if the quote is taken out of context or not" WTF? -1 for not trying. There's a panel discussion with: Erik Meijer (misc, head of Cloud Programmability Team at Microsoft) Gilad Bracha (Dart) Martin Odersky (most recently Scala) Anders Hejlsberg (Turbo Pascal, Delphi, C# etc) Peter Alvaro (researcher e.g. datalog) And some ungooglable twerp doesn't actually listen to it? Argument from authority seems spot-on when you're replying to something they said. Make that -2

roopeshv 14y ago
in all fairness, that sentence is said more like a passing comment and not a discussion topic
- willvarfar 14y ago
  I posted the original to reddit/r/javascript so I've got a point to defend ;) In the video, they do talk about tooling, IDEs, auto-completion, libraries, dynamic types, and so on. Refactoring tools come up repeatedly. So you can build up a richer context to the reasoning. There's even discussion about reasoning about systems made from components running on different machines, which is not far from what this Derek chap responds with as his perceived solution. Its not all tightly packed into a sound-bite.

dllthomas 14y ago

Certainly, large programs are harder to maintain than small programs. Certainly, modularity and encapsulation helps, in any language. The implication that, therefore, choice of language is irrelevant to maintainability is spurious.

roopeshv 14y ago
did you listen to the talk
vlisivka 14y ago
Definition of large program is "program, which is hard to maintain". So large programs are hard to maintain by definition.
- dllthomas 14y ago
  You're referring to a line I never drew. Programs can be larger or smaller in many dimensions - LoC, complexity, features... Other things being equal, the smaller program is easier to deal with. We don't need to say "these programs are large and these are small" to make valid inferences in this area.

bad_user 14y ago

Link-bait. The problem of composability has been debated to death and is in general recognized to be the biggest problem of our software industry. Even Unix-derived operating systems come these days with pretty big and monolithic pieces of software. Even Emacs is technically a big and monolithic piece of software, at least when compared to Vi. But Derick, You Write Large JavaScript Apps ... I write JavaScript applications that appear to be large. Not trying to make an argument about who Derick is, but he's arguing against Anders Hejlsberg, a very talented software engineer and language designer. Certainly we should be wary about appeals to authority (just like the one I've made), however let's not get ahead of ourselves and forget the shoulders of the giants on which we stand.

DanielRibeiro 14y ago

The original talk: http://css.dzone.com/articles/you-can-write-large-programs http://css.dzone.com/articles/you-can-write-large-programs Martin Odersky keeps a sober view on all of this. His insights on sound/unsound type systems is really good. Also, Peter Alvaro makes a very good complaint about having a distinction of library creators and every-day programmers, which the others seem to believe not only to be true, but also to be inevitable (I obviously side with Peter on this). The conversation is much better than this sad remark.

mickeyp 14y ago

I've had this discussion with co-workers before about scripting languages, and in particular Python, as that is what I am working with currently. I feel that once Python -- or indeed any loosey-goosey language that lack strong types -- programs grow beyond a certain size you easily fall into the "inconsistency trap", especially if you have many programmers working on the same code base. You have to be extra diligent with docstrings; unit tests and variable naming, or invent your own poor, ad hoc type checking with isinstance, or liberal use of exception handling if you insist on ensuring that Python's duck typing continues to work in your program. Invariably you'll end up with two camps: those who feel <dynamic lang> scales to large codebases, and those who do not; those in the former camp have (almost never) had to maintain a millions of lines of code before so they do not know just how helpful having a strict compiler is, and just how hard it is to refactor or infer the meaning of code due to the dynamic nature of the language. Linting will only get you so far. It's perfectly possible to write maintainable, large programs in dynamic languages, but it is infinitely harder than it should be.

reycharles 14y ago
Python is actually strongly typed. For example, 1+"1" will fail in python. Type errors will (usually) make the program crash. I believe this is a major plus over javascript when writing and maintaining large programs.
- mickeyp 14y ago
  Yes, crash at runtime. That's no good in a production environment when you can have hundreds of code paths and no real way of ensuring they are all correct. Mistakes happen, and code coverage tools are in my experience pretty useless at ensuring all code paths have been exercised (a theoretically futile task as well.) As for strongly typed- yes, that is true, but it is also dynamically typed, and combined with duck typing you're left with a philosophy that encourages interchangeable types provided the interface is similar. Strong typing come in many forms, and you can have strong types and still have a compiler there to help you out. But of course, no system is perfect. That's all well and good when you still have a complete, mental overview of the code and how it interacts at a macroscopic level. That's much harder to do when you go from 1 to many developers -- especially if you're developing code to be consumed by other developers.

willvarfar 14y ago

I struggle to maintain a large system in Python (which, at least, is strongly typed). My major banes are: * performance. You have a hard job retrofitting performance to Python * typos. Typos that survive my Integration Tests which can never have enough coverage. Stuff that just won't compile in a static language becomes a runtime issue on a dynamic language, and they can hide for months outside the happy path e.g. in some error handing code * poor libraries. I get nice warm happy feelings about various async server frameworks that last until I have to debug them and stare at their innards and realised they were contributed to and diluted by twits * pip/virtualenv doing a poor job with native code in modules At least it has namespaces / modules and such At least its not common for every 3rd party lib to want to squat on a function called $ And so on. Static typing is a major plus when you are beyond the prototyping stage and heading heading towards the release and maintenance phase. Which is why I'm on the look out for implicitly strongly statically typed languages that look like Python :)

mixmastamyk 14y ago
Try pyflakes, pylint, etc. They've helped me find a few typos in exception handlers that are rarely run.