  An algorithm is in-place, or runs in-situ, when it does not need any
additional memory to execute beyond a small constant amount. There are many
algorithms that are efficient because of this feature, therefore it is an
important aspect of an algorithm. In most programming languages, it is not
obvious when an algorithm can run in-place, and moreover it is often not clear
that the implementation respects that idea. In this paper we study interaction
nets as a formalism where we can see directly, visually, that an algorithm is
in-place, and moreover the implementation will respect that it is in-place. Not
all algorithms can run in-place however. We can nevertheless still use the same
language, but now we can annotate parts of the algorithm that can run in-place.
We suggest an annotation for rules, and give an algorithm to find this
automatically through analysis of the interaction rules.
