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    Fixed by not using string interpolation, seems the F# version here doesn't support it

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    Not a kata issue.

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    This doesn't seem like a kata issue, because the errors are coming from your code. I don't know F#, but reading the error messages leads me to believe that you're using a different version of F# locally, hence the errors.

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    Has F# been tested? I can solve the solution locally but when testing it I get this error:
    /home/codewarrior/program.fsx(43,29): error FS1160: This token is reserved for future use

    /home/codewarrior/program.fsx(65,76): error FS0035: This construct is deprecated: ':' is not permitted as a character in operator names and is reserved for future use

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    ok after looking at the other solutions I completely overthought this problem, spent a night on the red and found it particularly difficult for no reason - of course I should have just calculated the fib sequence in reverse. Sometimes a simple solution is missed

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    Not an issue, everything works correctly.

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    Nice simple explanation with unit testing. Good Kata, well done.

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    Approved

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    Well I spent more time trying to understand the question than coding, hacking it together piece by piece as my understanding of the question evolved. I notice a lot of problems on this site are like that. Briefer, simpler to understand questions but with complicated solutions would be a far nicer thing to encounter.

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    What a terribly worded Kata. "An array of numbers" is incorrect, it's an array of strings. For something like computer programming where precision is everything this is absurd.

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    Why are slow solutions often the #1 voted just because they contain the fewest lines of code? In terms of efficiency for the end user I'd be interested in seeing a category that solves a problem with the minimal execution time. An example of this is in C# where nearly every solution uses LINQ, which is slower than non-LINQ based solutions despite it being shorter.

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    i feel like since the data is so small for these tests, that run time is not super relevant. Run time for small sets of input is not a good indicator, it is when we talk about "sufficently" large enough data sets.

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    Works for me

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