Seeing that some are adding timings to the posted solutions. The APL solution I posted above (+/⍳1E9) takes 56 microseconds to execute on my system (checked by

Seeing that some are adding timings to the posted solutions. The APL solution I posted above (+/⍳1E9) takes 56 microseconds to execute on my system (checked by solving it 100,000 times in a loop). The interpreter is obviously not doing a huge memory and clock-cycle sucking expansion of a one billion element vector. This highlights another advantage of a symbolic language: Idioms or patterns within code can be recognized replaced with equivalent highly-efficient, highly-tuned operations. The above example is obviously solved by having the interpreter swap it out for the well-understood mathematical solution. Because of this the programmer can focus on the problem space rather than having to dork around with figuring out optimizations. Granted, this is a simple one for anyone with a decent math background, but it can get far more complex. Have a look at the famous Finn APL idiom library: http://aplwiki.com/FinnAplIdiomLibrary http://aplwiki.com/FinnAplIdiomLibrary An interpreter designer might very well decide to detect a good number of these idioms and execute highly tuned code instead of the memory and CPU-cycle hogging expansions that might result from running the actual code as written. In many ways I equate this to what happens when using a language like Verilog to design FPGA circuits. You are designing hardware, not software. FPGA compilers have inference engines that recognize certain structures to mean specific circuit constructs. It's a contract. We agree that when I write this I mean to ask that you instantiate that and everyone is happy.