Scientific progress calls for reproducing results. Due to limited
resources, this is difficult even in computational sciences. Yet,
reproducibility is only a means to an end. It is not enough by itself
to enable new scientific results. Rather, new discoveries must build
on reuse and modification of the state …
tl;dr:Reproducibilty is a noble cause and scientific
software a promising vessel. But excess of reproducibility can be at
odds with the housekeeping required for good software engineering.
Code that “just works” should not be taken for granted.
This post advocates for a progressive consolidation effort of
Christophe Pradal, Hans Peter Langtangen, and myself recently edited
a version of the
Journal of Computational Science on scientific software, in
particular those written in Python. We wrote an editorial
defending writing and publishing open source scientific software that
I wish to summarize here. The full text preprint is openly …