  Reiter's HS-Tree is one of the most popular diagnostic search algorithms due
to its desirable properties and general applicability. In sequential diagnosis,
where the addressed diagnosis problem is subject to successive change through
the acquisition of additional knowledge about the diagnosed system, HS-Tree is
used in a stateless fashion. That is, the existing search tree is discarded
when new knowledge is obtained, albeit often large parts of the tree are still
relevant and have to be rebuilt in the next iteration, involving redundant
operations and costly reasoner calls. As a remedy to this, we propose
DynamicHS, a variant of HS-Tree that avoids these redundancy issues by
maintaining state throughout sequential diagnosis while preserving all
desirable properties of HS-Tree. Preliminary results of ongoing evaluations in
a problem domain where HS-Tree is the state-of-the-art diagnostic method
suggest significant time savings achieved by DynamicHS by reducing expensive
reasoner calls.
