Enumeration on Trees with Tractable Combined Complexity and Efficient Updates
Abstract
We give an algorithm to enumerate the results on trees of monadic second-order (MSO) queries represented by nondeterministic tree automata. After linear time preprocessing (in the input tree), we can enumerate answers with linear delay (in each answer). We allow updates on the tree to take place at any time, and we can then restart the enumeration after logarithmic time in the tree. Further, all our combined complexities are polynomial in the automaton. Our result follows our previous circuit-based enumeration algorithms based on deterministic tree automata, and is also inspired by our earlier result on words and nondeterministic sequential extended variable-set automata in the context of document spanners. We extend these results and combine them with a recent tree balancing scheme by Niewerth, so that our enumeration structure supports updates to the underlying tree in logarithmic time (with leaf insertions, leaf deletions, and node relabelings). Our result implies that, for MSO queries with free first-order variables, we can enumerate the results with linear preprocessing and constant-delay and update the underlying tree in logarithmic time, which improves on several known results for words and trees. Building on lower bounds from data structure research, we also show unconditionally that up to a doubly logarithmic factor the update time of our algorithm is optimal. Thus, unlike other settings, there can be no algorithm with constant update time.
Cite
@article{arxiv.1812.09519,
title = {Enumeration on Trees with Tractable Combined Complexity and Efficient Updates},
author = {Antoine Amarilli and Pierre Bourhis and Stefan Mengel and Matthias Niewerth},
journal= {arXiv preprint arXiv:1812.09519},
year = {2019}
}
Comments
16 pages of main material, 37 references, 11 pages of appendix. This is the extended version with proofs of the PODS'19 paper. Except for minor rephrasings and formatting differences, the contents are exactly the same as the version published in the PODS'19 proceedings