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from the COBOL-is-often-fractionally-better dept.
https://medium.com/@bellmar/is-cobol-holding-you-hostage-with-math-5498c0eb428b
Face it: nobody likes fractions, not even computers.
When we talk about COBOL the first question on everyone's mind is always Why are we still using it in so many critical places? Banks are still running COBOL, close to 7% of the GDP is dependent on COBOL in the form of payments from the Centers for Medicare & Medicaid Services, The IRS famously still uses COBOL, airlines still use COBOL (Adam Fletcher dropped my favorite fun fact on this topic in his Systems We Love talk: the reservation number on your ticket used to be just a pointer), lots of critical infrastructure both in the private and public sector still runs on COBOL.
Why?
The traditional answer is deeply cynical. Organizations are lazy, incompetent, stupid. They are cheap: unwilling to invest the money needed upfront to rewrite the whole system in something modern. Overall we assume that the reason so much of civil society runs on COBOL is a combination of inertia and shortsightedness. And certainly there is a little truth there. Rewriting a mass of spaghetti code is no small task. It is expensive. It is difficult. And if the existing software seems to be working fine there might be little incentive to invest in the project.
But back when I was working with the IRS the old COBOL developers used to tell me: "We tried to rewrite the code in Java and Java couldn't do the calculations right."
[Ed note: The referenced article is extremely readable and clearly explains the differences between floating-point and fixed-point math, as well as providing an example and explanation that clearly shows the tradeoffs.]
(Score: 2) by DannyB on Monday September 16 2019, @06:03PM (1 child)
I have written calculations like you describe in a financial calculation. That calculation is a black box. It takes inputs, does an inexact calculation, to great precision, and then the results are fixed into some form of currency values that are the result(s) of that black box.
Everyone who does the same calculations (different languages, implementations, etc) will get the same results. But outside that black box, you're back to some kind of currency representation of money.
Values of money have always been integer data types since before recorded history. The age of computers did not change that.
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(Score: 2) by FatPhil on Tuesday September 17 2019, @07:05AM
I'd change that to "Values of money have always been values representing integer multiples of an atomic unit of value since before recorded history." as we've usually chosen a fixed point representation. If the base unit of currency was the cent, rather than the dollar, then many of the issues people bring up would simply evaporate. This is because decimal-heads love saying stupid things like "you can't represent $0.01 exactly in binary", which is patently false if you're representing cents. If you encounter side effects like "1 dollar (100)" * "1 dollar (100)" = "100 dollars (10,000)", then you are almost certainly doing something wrong, as there's no such thing as a square dollar.
But you seem to get it - firstly you need an exact representation for every value that you wish to represent (can be fixed point, can be floating point suitably scaled, can be decimal FP, can be integer). Binary FP based on dollars is not such a beast - noone's denying that. Once you've got that, then operate on those values using whatever is most accurate. And given that you want to avoid overflow at all costs, that's almost certainly FP. And as I've mentioned elsewhere, binary provably does better than decimal.
The problem is when people fail to perform that first decision-making step correctly. Some languages protect idiot programmers against this better than others. I personally think it's better to just not hire idiot programmers, as they'll make a mistake elsewhere.
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