# Linear Bounded Composition of Tree-Walking Tree Transducers: Linear Size   Increase and Complexity

**Authors:** Joost Engelfriet, Kazuhiro Inaba, Sebastian Maneth

arXiv: 1904.09203 · 2019-12-13

## TL;DR

This paper proves that compositions of tree-walking tree transducers can be realized with linear size intermediate results, impacting their expressiveness and computational complexity.

## Contribution

It introduces the concept of linear bounded composition for tree-walking transducers and analyzes the complexity and expressiveness of their compositions.

## Key findings

- Compositions can be realized with intermediate results of linear size.
- Linear size increase functions can be realized by a single deterministic transducer.
- Deterministic compositions are computable in linear time and space; nondeterministic ones in polynomial time and linear space.

## Abstract

Compositions of tree-walking tree transducers form a hierarchy with respect to the number of transducers in the composition. As main technical result it is proved that any such composition can be realized as a linear bounded composition, which means that the sizes of the intermediate results can be chosen to be at most linear in the size of the output tree. This has consequences for the expressiveness and complexity of the translations in the hierarchy. First, if the computed translation is a function of linear size increase, i.e., the size of the output tree is at most linear in the size of the input tree, then it can be realized by just one, deterministic, tree-walking tree transducer. For compositions of deterministic transducers it is decidable whether or not the translation is of linear size increase. Second, every composition of deterministic transducers can be computed in deterministic linear time on a RAM and in deterministic linear space on a Turing machine, measured in the sum of the sizes of the input and output tree. Similarly, every composition of nondeterministic transducers can be computed in simultaneous polynomial time and linear space on a nondeterministic Turing machine. Their output tree languages are deterministic context-sensitive, i.e., can be recognized in deterministic linear space on a Turing machine. The membership problem for compositions of nondeterministic translations is nondeterministic polynomial time and deterministic linear space. The membership problem for the composition of a nondeterministic and a deterministic tree-walking tree translation (for a nondeterministic IO macro tree translation) is log-space reducible to a context-free language, whereas the membership problem for the composition of a deterministic and a nondeterministic tree-walking tree translation (for a nondeterministic OI macro tree translation) is possibly NP-complete.

## Full text

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## References

75 references — full list in the complete paper: https://tomesphere.com/paper/1904.09203/full.md

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Source: https://tomesphere.com/paper/1904.09203