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All the Perl that's Practical to Extract and Report

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  • Random functions require random tests, of course.

    Just like documentation: if it was hard to write, it should be hard to read.

  • Tests of random functions, that is to say functions specified to act randomly, must be STATISTICAL tests. Run the function a large number of times ($N), and check that the basic and not-so-basic statistics match the model you require of your function under test.

    Pseudo code for an inadequate number of tests of an imaginary model, assumed not unlike a bell-curve - your mileage WILL vary -

    $fut= \&FunctionUnderTest;
    my @X= map { $fut->() } 1..$N ;

    use Acme::Statistics; # Fantasy package that provides

    # I had a sig when sigs were cool
    use Sig;
    • Interesting. I was just talking to a coworker about that. It's been years since statistics classes and I was struggling to remember the formulae involved in calculating what I was interested in. I wasn't thinking of a distribution under a bell curve so much as I was thinking "if X might not be correct, how many times do I need to calculate X to ensure the odds of it being incorrect are acceptably minimized?" More inportantly, I can't have randomly failing tests, but I'm quite happy to have a test which

  • Intelligently designed!