On Sun, Nov 23 2014, Stefan Karpinski <[email protected]> wrote: > On Sun, Nov 23, 2014 at 6:02 AM, Christian Peel <[email protected]> wrote: > >> Milan, >> >> Thanks for the comments. I also am confident that info about what line >> errors occur on will improve. >> > > For some context, the reason traditional dynamic systems like e.g. Matlab > or Python, don't have this issue is that they use interpreters and > literally walk through a fairly faithful representation of the code you > wrote, including line number annotations. Thus, when an error occurs, it's > a trivial matter to report the line number you are currently interpreting – > the parsed code representation is the exact thing you're operating on when > the error occurs. Moreover, to give a full stack trace, you simply need to > walk back through the stack data structure that the interpreter maintains > as it executes the program. > > In a JIT system like Julia, things are quite different. By the time your > code is running, it no longer closely resembles the code you wrote and > there is no interpreter and the "stack" is the actual stack. All of this is > what gives you C-like performance. When an error occurs, the error message > and stack trace have to be determined from the machine code that is > currently executing and the stack trace is derived from *the* stack, not > some data structure. All this is further complicated by the fact that > LLVM's JIT does not tend to produce debug data quite as well as the static > compilation infrastructure does. People don't seem to use debuggers on > JITed code or particularly care about backtraces, so we're pushing the > envelope here, but things are getting better quite steadily.
I am wondering if the approach used by Common Lisp implementations could be applicable in Julia. In Common Lisp, one can have various optimization and debug level settings, eg (optimize (speed 3) (safety 0) (debug 0)) will produce very fast code (comparable to C on modern implementations if type info is available), with the trade-off that one has very little debug information, while (optimize (debug 3)) does the opposite. Of course, the function needs to be recompiled for these to take effect, but given that you can always modify the image in a backtrace (AFAIK you can do the same in Julia), it works fine in practice. Best, Tamas
