Serious look at programming statistics.

[btiffin]

Well, statistics ... take this as biased. But for those that care, this white paper might help (especially table 8.7) make some decisions on what to learn next.

http://www.jsayles.com/ibm/cobol/COBOL2009.htm

Another pretty neat link (again, assume author bias ... it's the way statistical analysis works ... for instance, I place wayyy less importance on the concept of verbosity and conciseness of expression over quick grok, a much harder aspect to quantify. Place your opinions on the graphs while you look them over.) Again, this page is a good read for those pondering on where they may gain the biggest bang for the buck when picking a career path ... umm, but don't just accept the conclusions, ponder the results and the style of information gathering. Still neat and chock full of insights, particularly for those with a bent towards open programming systems.

http://gmarceau.qc.ca/blog/2009/05/speed-size-and-dependability-of.html

Cheers

[Prabhakar Ragde]

Note that the author of the meta-study in the second link chose PLT Scheme as the language to use to generate the data...

[wtd]

I find it interesting to note where O'Caml ranks. It appears to be if not the best, then one of the top three.

Maybe I've been onto something for the last few years.