Over on O'Reilly Radar, Nat Torkington recently posted:
According to a blog post by (update: a friend of) one of the developers, Amazon's SimpleDB is built on Erlang. Cool! Another datapoint for the trend we see towards parallel-capable languages like Erlang and Haskell.
"Parallel-capable"? I know the arguments---values in pure functional languages (PFLs) are immutable once created, so there can't be race conditions, so parallel programming is easier, and parallel programs will scale better---but I have yet to see any data to substantiate that oft-repeated meme. I wrote a book about parallel programming in the early 90s, and have maintained a more-than-casual interest in the topic ever since (mostly through work with computational scientists). I don't believe that PFLs make non-trivial parallel programs easier to write. I don't believe they make parallel programming harder, either, and the reason I don't is that I haven't seen any empirical studies of real programmers writing real programs that point either way. I hereby offer a very nice bottle of wine and/or all seven seasons of Buffy the Vampire Slayer to the first person to conduct a study rigorous enough to be accepted as a senior undergraduate project in psychology---a standard which, sadly, most discussion of the merits of various programming languages, tools, and paradigms signally fails to meet.
Note: if you'd like to know what those standards are---i.e., what kind of evidence you should require someone who's pushing the software equivalent of a cure for baldness to give you---please have a look at:
B.A. Kitchenham, S.L. Pfleeger, L.M. Pickard, P.W. Jones, D.C. Hoaglin, K. El Emam, and J. Rosenberg: "Preliminary guidelines for empirical research in software engineering". IEEE Transactions on Software Engineering, 28(8), August 2002.
Barbara A. Kitchenham, Tore Dyba, and Magne Jorgensen: "Evidence-Based Software Engineering". Proc. 26th International Conference on Software Engineering (ICSE'04), 2004.