4 ms·

100+ points, first place on front page, and not a single comment. Now that's rare. I assume everyone is excitedly browsing https://github.com/llvm-mirror/llvm

100+ points, first place on front page, and not a single comment. Now that's rare. I assume everyone is excitedly browsing https://github.com/llvm-mirror/llvm https://github.com/llvm-mirror/llvm? ;) ( the official repo at http://llvm.org/git/llvm http://llvm.org/git/llvm is down)

tomcam 10y ago
Guilty as charged! This is so so welcome to an old school compiler guy
- pyvpx 10y ago
  as someone who has never written a compiler but has an intense interest in doing so, this is also very welcomed!
  - tomcam 10y ago
    Now is is a great time to write your first compiler. The wealth of tools and docs these days is breathtaking. Give it a go!
    - kenver 10y ago
      I wrote a toy compiler a very long time ago and I'd like to try again. Do you have any links/recommendations for resources that would be a good starting place?
      - fjrieiekd 10y ago
        LLVM Kaleidoscope, or if you'd like to start with your own toy CPU, then nand2tetris on Coursera.
  - csmattryder 10y ago
    I bet you have, but if not, do yourself a favour and grab a copy of "Compilers: Principles, Techniques and Tools" aka "The Dragon Book". Still got my copy from uni, dog-eared and sticky-noted throughout.
    - tom_mellior 10y ago
      I recall the classic 1986 edition of the Dragon Book spending waaaay too much time on boring details of lexing and parsing. I think it turned many people off the interesting aspects of compilers. It also had an interval-based formulation of data-flow analysis that nobody uses, possibly because it's (a) more complex than worklist iteration, and (b) not applicable to irreducible control flow graphs. Are newer editions better and more focused on interesting solutions to interesting problems?
      - rwallace 10y ago
        Try the Tiger Book instead (a.k.a. 'Modern compiler implementation in C', or there are Java or ML versions if those are more to your taste). It has a better balance: more to the point treatment of lexing and parsing, leaving more space for a more comprehensive treatment of optimization and code generation.
        pjmlp 10y ago
        I second it, even if the book has a few issues here and there, it was one of the best books I read on the subject.
    - astrange 10y ago
      I recommend making sure to avoid reading this book, it spends all its time making mountains out of molehills in the easy parts and leaves out the hard parts. How did they write so many pages about text parsing? The books by Appel and Louden (forgot the names) are good.
akavel 10y ago
I have a theory that since the introduction of "favorites" on HN, people more often fave something as a "Read Later [Totally Some Day, Really, Only Just... Not Today... But I Will Soo Come Back To It]" bookmark. Thus "lists of 100 interesting books", "algorithms you must know", "write yourself an OS in 99 days", etc. etc., I feel they have tendency to behave like that. (The theory is based partially on what I observed looking at myself ;). But please note it's totally just a loose theory, I don't have data or whatever, nor I'd judge this as bad or good. Only observing with curiosity.
- pjmorris 10y ago
  Anec-data: I favorite things as a "Read Later [Totally Some Day, Really, Only Just... Not Today... But I Will Soo Come Back To It]" bookmark. Well, mostly. I do read some percentage of the articles and comments as I go, and I do go back to see updates to the comments... and to, every once in awhile, read the fave'd article. I feel like I ought to have a side project that uses my HN favorites, pinboard links, comments, etc to seed a recommendation engine of 'other stuff you should probably read'.
  - ChickeNES 10y ago
    > I feel like I ought to have a side project that uses my HN favorites, pinboard links, comments, etc to seed a recommendation engine of 'other stuff you should probably read'. I would totally use it. I considered writing something myself, but I have too many on-going side projects as it is unfortunately.
pag 10y ago
I always use this: https://code.woboq.org/llvm/llvm/ https://code.woboq.org/llvm/llvm/

tomcam 10y ago

Guilty as charged! This is so so welcome to an old school compiler guy

pyvpx 10y ago
as someone who has never written a compiler but has an intense interest in doing so, this is also very welcomed!
- tomcam 10y ago
  Now is is a great time to write your first compiler. The wealth of tools and docs these days is breathtaking. Give it a go!
  - kenver 10y ago
    I wrote a toy compiler a very long time ago and I'd like to try again. Do you have any links/recommendations for resources that would be a good starting place?
    - fjrieiekd 10y ago
      LLVM Kaleidoscope, or if you'd like to start with your own toy CPU, then nand2tetris on Coursera.
- csmattryder 10y ago
  I bet you have, but if not, do yourself a favour and grab a copy of "Compilers: Principles, Techniques and Tools" aka "The Dragon Book". Still got my copy from uni, dog-eared and sticky-noted throughout.
  - tom_mellior 10y ago
    I recall the classic 1986 edition of the Dragon Book spending waaaay too much time on boring details of lexing and parsing. I think it turned many people off the interesting aspects of compilers. It also had an interval-based formulation of data-flow analysis that nobody uses, possibly because it's (a) more complex than worklist iteration, and (b) not applicable to irreducible control flow graphs. Are newer editions better and more focused on interesting solutions to interesting problems?
    - rwallace 10y ago
      Try the Tiger Book instead (a.k.a. 'Modern compiler implementation in C', or there are Java or ML versions if those are more to your taste). It has a better balance: more to the point treatment of lexing and parsing, leaving more space for a more comprehensive treatment of optimization and code generation.
      - pjmlp 10y ago
        I second it, even if the book has a few issues here and there, it was one of the best books I read on the subject.
  - astrange 10y ago
    I recommend making sure to avoid reading this book, it spends all its time making mountains out of molehills in the easy parts and leaves out the hard parts. How did they write so many pages about text parsing? The books by Appel and Louden (forgot the names) are good.

akavel 10y ago

I have a theory that since the introduction of "favorites" on HN, people more often fave something as a "Read Later [Totally Some Day, Really, Only Just... Not Today... But I Will Soo Come Back To It]" bookmark. Thus "lists of 100 interesting books", "algorithms you must know", "write yourself an OS in 99 days", etc. etc., I feel they have tendency to behave like that. (The theory is based partially on what I observed looking at myself ;). But please note it's totally just a loose theory, I don't have data or whatever, nor I'd judge this as bad or good. Only observing with curiosity.

pjmorris 10y ago
Anec-data: I favorite things as a "Read Later [Totally Some Day, Really, Only Just... Not Today... But I Will Soo Come Back To It]" bookmark. Well, mostly. I do read some percentage of the articles and comments as I go, and I do go back to see updates to the comments... and to, every once in awhile, read the fave'd article. I feel like I ought to have a side project that uses my HN favorites, pinboard links, comments, etc to seed a recommendation engine of 'other stuff you should probably read'.
- ChickeNES 10y ago
  > I feel like I ought to have a side project that uses my HN favorites, pinboard links, comments, etc to seed a recommendation engine of 'other stuff you should probably read'. I would totally use it. I considered writing something myself, but I have too many on-going side projects as it is unfortunately.

pag 10y ago

I always use this: https://code.woboq.org/llvm/llvm/ https://code.woboq.org/llvm/llvm/