4 ms·

> Some well intentioned papers share code which is hard to run years afterwards. Umm, not really? How many years are we talking about here? Because even Cobol

> Some well intentioned papers share code which is hard to run years afterwards. Umm, not really? How many years are we talking about here? Because even Cobol is runnable. Sure some OS related quirks may need changing but getting the raw source is much more likely to expose a subtle flaw in the researcher's method than just the equations. For example, an incorrect negative check (to string vs < 0) or an off by one error.

wizzwizz4 5y ago
Don't think COBOL; think Python 2.1 (not 2.2) with this specific version of PIL, and some of the code implemented as a CPython module (for speed) in C that only compiles properly with one specific EGCS fork that adds support for IA-64. Parts of the code are written in slightly-buggy inline IA-64 assembly, but it's okay because after a system call, that particular operating system makes sure those registers are zeroed each loop iteration, if Python's line-buffering its `print`s so that the system call gets consistently run. Also, the Python script crashes on loading the data files unless there are two (but not more than two) spaces in its full file path. This is not documented anywhere.
- mach1ne 5y ago
  This comment could well have come from Chief O'Brien's mouth.
- rini17 5y ago
  So? Nothing a CS grad couldn't manage, that sounds like real problems they grapple with. Still a notch better than no code.
- lodovic 5y ago
  Indeed, that's not proper science, too many moving parts. If it cannot be easily replicated by anyone at any time, it is just an experiment which would need more refinement to get published. No experiment should be accepted if it requires a Rube-Goldberg machine.
- kergonath 5y ago
  Yeah. I can easily run FORTRAN code from my PhD supervisor's PhD supervisor, written way back in the 1980s, but I cannot run some of the Python scripts written by a post-doc 10 years ago. It's a mess of abandoned libraries and things that work only with some specific versions of some libraries, and compiled modules that rely on the dodgy behaviour of an old compiler. Perl seems to be better, if only because people used to rely much less on external libraries. But properly running code is not the solution either. I can count on the fingers of one had the downloads of some of the codes we've published (easily compilable modern Fortran), and AFAIK nobody ever published anything using them. Having a multitude of codes available does not mean much if nobody runs them, assuming they can be compiled. And I would guarantee that none of the scientists who download these codes would be able to understand what they do in any detail.

wizzwizz4 5y ago

Don't think COBOL; think Python 2.1 (not 2.2) with this specific version of PIL, and some of the code implemented as a CPython module (for speed) in C that only compiles properly with one specific EGCS fork that adds support for IA-64. Parts of the code are written in slightly-buggy inline IA-64 assembly, but it's okay because after a system call, that particular operating system makes sure those registers are zeroed each loop iteration, if Python's line-buffering its `print`s so that the system call gets consistently run. Also, the Python script crashes on loading the data files unless there are two (but not more than two) spaces in its full file path. This is not documented anywhere.

mach1ne 5y ago
This comment could well have come from Chief O'Brien's mouth.
rini17 5y ago
So? Nothing a CS grad couldn't manage, that sounds like real problems they grapple with. Still a notch better than no code.
lodovic 5y ago
Indeed, that's not proper science, too many moving parts. If it cannot be easily replicated by anyone at any time, it is just an experiment which would need more refinement to get published. No experiment should be accepted if it requires a Rube-Goldberg machine.
kergonath 5y ago
Yeah. I can easily run FORTRAN code from my PhD supervisor's PhD supervisor, written way back in the 1980s, but I cannot run some of the Python scripts written by a post-doc 10 years ago. It's a mess of abandoned libraries and things that work only with some specific versions of some libraries, and compiled modules that rely on the dodgy behaviour of an old compiler. Perl seems to be better, if only because people used to rely much less on external libraries. But properly running code is not the solution either. I can count on the fingers of one had the downloads of some of the codes we've published (easily compilable modern Fortran), and AFAIK nobody ever published anything using them. Having a multitude of codes available does not mean much if nobody runs them, assuming they can be compiled. And I would guarantee that none of the scientists who download these codes would be able to understand what they do in any detail.