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copied!<p>1.) Scripting languages are popular these days for most things due to better hardware. Perl/Python/Lisp are prevalent for lightweight applications (automation, light computation); I see a lot of Perl at my work (computational EM) since we like Unix/Linux. For performance stuff, C/C++/Fortran are typically used. For parallel computing, well, we usually manually parallelize runs in EM as opposed to having a program implicitly do it (ie split up the jobs by look angle when computing radar cross sections).</p> <p>2.) We just kind of throw people into the mix here. A lot of the code we have is very messy, but scientists are typically a scatterbrained bunch that don't mind that sort of thing. Not ideal, but we have things to deliver and we're severely understaffed. We're slowly getting better.</p> <p>3.) We use SVN; however, we do not have bug tracking software. About as good as it gets for us is a txt file that tells you where bugs specific bugs are.</p> <p>4.) My suggestion for implementing best practices for scientists: <strong>do it slowly</strong>. As scientists, we typically don't ship products. <strong>No one in science makes a name for himself by having clean, maintainable code</strong>. They get recognition from the results of that code, typically. They need to see justification for spending time on learning software practices. Slowly introduce new concepts and try to get them to follow; they're scientists, so after their own empirical evidence confirms the usefulness of things like version control, they will begin to use it all the time! </p>

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