NaNs, Infinities, and Negative Numbers In Loan Calculators

I’ve encountered several NaNs over the years in the normal course of using various websites and apps. I’ve only documented two of them: one in a media player, and one in a podcast app. I recently ran into another one using a loan calculator website. Rather than reporting on just that one, I decided to look for more and report on anything I found all at once.

I found many more errors — NaNs, but also infinites, negative numbers, and one called “incomplete data”, whatever that means — all on websites within the top Google search results for “loan calculator”. All I had to do to elicit these errors was to enter large numbers. (And in one case, simply including a dollar sign.) All of the errors arise from the use of floating-point arithmetic combined with unconstrained input values. Some sites even let me enter numbers in scientific notation, like 1e308, or even displayed them as results.

Floating point error in loan calculator

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Incorrect Hexadecimal to Floating-Point Conversions in David Gay’s strtod()

I wrote about Visual C++ incorrectly converting hexadecimal constants at the normal/subnormal double-precision floating-point boundary. It turns out that David Gay’s strtod() also has a problem with the same inputs, converting them all to 0 instead of 0x1p-1022.

I have emailed Dave Gay to report the problem; I will update this post when he responds.

Incorrect Hexadecimal to Floating-Point Conversions in Visual C++

Martin Brown, through a referral on his Stack Overflow question, contacted me about incorrect hexadecimal to floating-point conversions he found in Visual C++, specifically conversions using strtod() at the normal/subnormal double-precision floating-point boundary. I confirmed his examples, and also found an existing problem report for the issue. It is not your typical “off by one ULP due to rounding” conversion error; it is a conversion returning 0 for a non-zero input or returning numbers with exponents off by binary orders of magnitude.

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