It does survive, in a certain sense, in scientific programming and data science. Both iPython notebooks and Rmarkdown are a sort of literate programming, although with the emphasis on the text more than the code. In that setting, the executable artifact is not really more important than the explanation of why the code does what it does, so the extra overhead is justifiable.

Rmarkdown example: http://kbroman.org/knitr_knutshell/pages/Rmarkdown.html

iPython notebook example: http://nbviewer.ipython.org/github/empet/Math/blob/master/Do...