  One popular technique to solve temporal planning problems consists in
decoupling the causal decisions, demanding them to heuristic search, from
temporal decisions, demanding them to a simple temporal network (STN) solver.
In this architecture, one needs to check the consistency of a series of STNs
that are related one another, therefore having methods to incrementally re-use
previous computations and that avoid expensive memory duplication is of
paramount importance. In this paper, we describe in detail how STNs are used in
temporal planning, we identify a clear interface to support this use-case and
we present an efficient data-structure implementing this interface that is both
time- and memory-efficient. We show that our data structure, called \deltastn,
is superior to other state-of-the-art approaches on temporal planning sequences
of problems.
