Tree transducers and tree languages

Tree transducers (automata which read finite labeled trees and output finite labeled trees) are used to define a hierarchy of families of “tree languages” (sets of trees). In this hierarchy, families generated by “top-down” tree transducers (which read trees from the root toward the leaves) alternate with families generated by “bottom-up” tree transducers (which read trees from the leaves toward the root). A hierarchy of families of string languages is obtained from the first hierarchy by the “yield” operation (concatenating the labels of the leaves of the trees). Both hierarchies are conjectured to be infinite, and some results are presented concerning this conjecture. A study is made of the closure properties of the top-down and bottom-up families in the hierarchies under various tree and string operations. The families are shown to be closed under certain operations if and only if the hierarchies are finite

Top-down tree transducers with regular look-ahead

Top-down tree transducers with regular look-ahead are introduced. It is shown how these can be decomposed and composed, and how this leads to closure properties of surface sets and tree transformation languages. Particular attention is paid to deterministic tree transducers

Pushdown machines for the macro tree transducer

The macro tree transducer can be considered as a system of recursive function procedures with parameters, where the recursion is on a tree (e.g., the syntax tree of a program). We investigate characterizations of the class of tree (tree-to-string) translations which is induced by macro tree transducers (macro tree-to-string transducers, respectively). For this purpose we define several pushdown machines of which the control is recursive without parameters, or even iterative, and which work on a generalized pushdown as storage. Because of the relevance for semantics of programming languages, we stress (besides the nondeterministic case) the study of machines for the total deterministic macro tree(-to-string) transducer, which translates every input tree into exactly one output tree (string, respectively). Finally, we characterize the n-fold composition of total deterministic macro tree transducers by recursive pushdown machines with an iterated pushdown as storage, which is a pushdown of pushdowns of … of pushdowns

Linear context-free rewriting systems and deterministic tree-walking transducers

We show that the class of string languages generated by linear context-free rewriting systems is equal to the class of output languages of deterministic tree- walking transducers. From equivalences that have previously been established we know that this class of languages is also equal to the string languages generated by context-free hypergraph grammars, multicomponent tree-adjoining grammars, and multiple contextfree grammars and to the class of yields of images of the regular tree languages under finite-copying top- down tree transducers

The copying power of one-state tree transducers

One-state deterministic top-down tree transducers (or, tree homomorphisms) cannot handle "prime copying," i.e., their class of output (string) languages is not closed under the operation L → {$(w$)f(n) w ε L, f(n) ≥ 1}, where f is any integer function whose range contains numbers with arbitrarily large prime factors (such as a polynomial). The exact amount of nonclosure under these copying operations is established for several classes of input (tree) languages. These results are relevant to the extended definable (or, restricted parallel level) languages, to the syntax-directed translation of context-free languages, and to the tree transducer hierarchy.\ud \u

Three hierarchies of transducers

Composition of top-down tree transducers yields a proper hierarchy of transductions and of output languages. The same is true for ETOL systems (viewed as transducers) and for two-way generalized sequential machines

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

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

Deciding Equivalence of Linear Tree-to-Word Transducers in Polynomial Time

We show that the equivalence of deterministic linear top-down tree-to-word transducers is decidable in polynomial time. Linear tree-to-word transducers are non-copying but not necessarily order-preserving and can be used to express XML and other document transformations. The result is based on a partial normal form that provides a basic characterization of the languages produced by linear tree-to-word transducers.Comment: short version of this paper will be published in the proceedings of the 20th Conference on Developments in Language Theory (DLT 2016), Montreal, Canad

Streaming Tree Transducers

Theory of tree transducers provides a foundation for understanding expressiveness and complexity of analysis problems for specification languages for transforming hierarchically structured data such as XML documents. We introduce streaming tree transducers as an analyzable, executable, and expressive model for transforming unranked ordered trees in a single pass. Given a linear encoding of the input tree, the transducer makes a single left-to-right pass through the input, and computes the output in linear time using a finite-state control, a visibly pushdown stack, and a finite number of variables that store output chunks that can be combined using the operations of string-concatenation and tree-insertion. We prove that the expressiveness of the model coincides with transductions definable using monadic second-order logic (MSO). Existing models of tree transducers either cannot implement all MSO-definable transformations, or require regular look ahead that prohibits single-pass implementation. We show a variety of analysis problems such as type-checking and checking functional equivalence are solvable for our model.Comment: 40 page