Interestingly, I believe the majority of languages you’ve quoted do actually have the same “problem” - they just mask it by showing fewer decimals than would be required to accurately represent the true number. There is not one single language intended for numerical analysis that I know of (SAS, R, S, Matlab, Mathematica, Maxima, Octave, SPSS,… a few others), not one, that allows for incorrect arithmetic of the kind I showed you above. I am using R language as an example because R is widely utilized in Pharma when regulations matter and this is one language they use to have their models approved. They might ask the following question and rightly so, “ wait a minute, you are telling me that my model can be mathematically correct but that I cannot expect mathematically correct results?” If now we mention Julia speed they only thing they are going to hear is how fast Julia fails. These people need to have their models approved by regulatory bodies, how do you think they will react when they find out that Julia, by design, accepts 1 + 1 = 2.12 ? julia> 1/(1-10^49/10^63) + 1/(1-10^49/10^63) # ~1 + ~1 Well, now you have found the first one, I work for Big Pharma and in some of my past projects closely so to the Pharmacokinetics and Pharmacodynamics crowd. While they have many concerns, I can’t say that anyone in any of those industries has ever expressed concern about integer overflow as a regulatory issue. At this point I’ve been involved in a lot of discussions with customers using Julia in a variety of heavily regulated industries-finance, pharma, medicine, insurance, aviation, aerospace, etc.
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