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Billennium's Over - Anything Break?

An Anonymous Coward writes: "The billennium party at OpenProjects.Net rocked! Check out the log for the whole event over here. Please don't forget to use one of the mirrors. Thanks :-)" Well, anyone have anything break due to the rollover?

3 of 265 comments (clear)

  1. yes... i broke... by CSIP · · Score: 1, Offtopic

    its just wrong to see a unix timestamp start with a 1 im gonna end up trying to debug a problem that doesnt exist...

    --
    "Nyquil - The stuffy, sneezy, why-the-hell-is-the-room-spinning medicine."
  2. Concorde Travelling-Salesman solver by eigenkarma · · Score: 0, Offtopic

    Concorde is a nice package for solving travelling salesman problem. It has a fast implementation of chained Lin-Kernighan heuristic. I've been using it extensively in the last few months and starting this morning (Australia time), it's been crashing randomly, even when applied to the same data that worked fine last week. I recompiled it on various unices (Linux, DEC) and same thing still happened. Because the program uses random number extensively to create new paths, there must be something wrong with the way it generate the seed. Luckily, it has an option to fix the random number seed, and when it automatically chooses one, it also displays it.
    Looking at the numbers, it's not hard to make the connection.

  3. Re:My mail client - pronto broke. by smallpaul · · Score: 1, Offtopic

    As a Python bigot (flame-bait me!) I'll point out that Perl, PHP and a few other Unix-y scripting languages are especially prone to this problem because they don't distinguish between strings and integers. I always knew that there would be a payoff in Python requiring me to explicitly convert.

    This seems like a cheap shot but really there is a systemic issue here. Perl trades robustness for succintness whereas Python tends to require you to say what you mean explicitly. With perfect programmers there would be no difference. In the real world, programmers are not perfect and a language that helps you to find potential problems can yield quantitatively more robust code.