've tracked down an interesting discrepancy between an AFL formula inputted division from AFL and that same formula inputted division in a C++ plugin function.
The AFL formula receiving the input in both cases is essentially computing the length of a line,
length = sqrt((x1 - x2)^2 + (y1 - y2)^2))
The input into this formula is the result of a division, eg., num/denom.
Here's the interesting part. The output of this formula is slightly different depending on whether this division is done by a C++ plugin using the C++ / operator versus whether it is done using the AmiBroker / operator. I've traced out the inputs to the function in both cases and they are the same to at least 5 decimal places. Also, the results if I use AFL all the way through are the same everytime I run it, while the results if I do C++ can be slightly different from run to run (even though the inputs print out as the same every run).
I'm pretty sure at this point I'm seeing a floating point error. I'm not sure what kind though. With floating point error, I'd expect the same output error every time. I've found the following paper online and know I can rewrite the formula to make it less sensitive to floating point differences:
What Every Computer Scientist Should Know About Floating-Point Arithmetic
My question is whether I can be doing something more silver bullet-like to avoid these kinds of problems? For example, should I be using double precision in C++ for the arithmetic and then convert to float before passing results back to AmiBroker? Is AmiBroker doing something special which allows it to produce stable results when I use AFL's / operator while I get slightly different results if I produce the input using the C++ / operator? If so, can I mirror AB's arithmetic strategy in my plugin to avoid any problems?
Posted by: rosenberggregg@yahoo.com
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