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Meet, hack, organize this new Haskell meetup group. RSVP required.

Want to meet and share tips, ideas and code with other Haskell hackers. So do we!

For this first meeting we will be strictly head count limited. MUST RSVP to attend. BUT, don't worry, we plan to expand the group size to fully meet demand when Hacker Dojo moves to a new location (very soon).

Check back for more details. Here I will be summarizing the suggestions you make on how this group should be organized. Please make your own suggestions in the RSVP email and they will be anonymized or openly discusss in the in discussions section here on here on meetup.com.

If we can get enough organizational feedback in advance, there will be more hacking, and less yakking about admin stuff.

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  • Tim S.

    Looking forward to seeing you tonight. Here's a tentative the schedule for tonight...
    6:00 mingle
    6:15 Tim, welcome, discussion about future schedule, format
    6:30 Conal, Inventing matrix operations – deriving How from What
    7:30 Greg, The shelly package
    8PM meetup officially ends, but people can hang out.

    --Tim
    PS If you can't make it pls. set your RSVP to 'Not Going'. This will allow wait listed folks to join in.

    November 15, 2012

  • Conal E.

    About my talk:

    Title: Inventing matrix operations – deriving How from What

    Abstract:

    Programs have two dimensions (among others): the What and the How. Correctness is a relationship between What and How, and efficiency is attained (without loss of correctness) by navigating in the space of Hows that are compatible with a What. Programming, however, requires precision about how but not about what, and so programmers are often much more conscious about how to solve problems than what problems they’re solving. Consequently, programming tends to proceed haphazardly via guesses, hand-waved justifications, and testing – more akin to tribal lore and craft than to math and engineering. This talk illustrates an alternative, which is principled derivation of implementations from specifications, via the example of matrix operations. The techniques used are widely applicable as means to discover correct algorithms and to more deeply understand known algorithms.

    November 13, 2012

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