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

Output String Languages of Compositions of Deterministic Macro Tree Transducers

The composition of total deterministic macro tree transducers gives rise to a proper hierarchy with respect to their output string languages (these are the languages obtained by taking the yields of the output trees). There is a language not in this hierarchy which can be generated by a (quite restricted) nondeterministic string transducer, namely, a two-way generalized sequential machine. Similar results hold for attributed tree transducers, for controlled EDT0L systems, and for YIELD mappings (which proves properness of the IO-hierarchy). Witnesses for the properness of the macro tree transducer hierarchy can already be found in the latter three hierarchies

Dependency structures and lexicalized grammars

In this dissertation, we show that that both the generative capacity and the parsing complexity of lexicalized grammar formalisms are systematically related to structural properties of the dependency structures that these formalisms can induce. Dependency structures model the syntactic dependencies among the words of a sentence. We identify three empirically relevant classes of dependency structures, and show how they can be characterized both in terms of restrictions on the relation between dependency and word-order and within an algebraic framework. In the second part of the dissertation, we develop natural notions of automata and grammars for dependency structures, show how these yield infinite hierarchies of ever more powerful dependency languages, and classify several grammar formalisms with respect to the languages in these hierarchies that they are able to characterize. Our results provide fundamental insights into the relation between dependency structures and lexicalized grammars.In dieser Arbeit zeigen wir, dass sowohl die Ausdrucksmächtigkeit als auch die Verarbeitungskomplexität von lexikalisierten Grammatikformalismen auf systematische Art und Weise von strukturellen Eigenschaften der Dependenzstrukturen abhängen, die diese Formalismen induzieren. Dependenzstrukturen modellieren die syntaktischen Abhängigkeiten zwischen den Wörtern eines Satzes. Wir identifizieren drei empirisch relevante Klassen von Dependenzstrukturen und zeigen, wie sich diese sowohl durch Einschränkungen der Interaktion zwischen Dependenz und Wortstellung, als auch in einem algebraischen Rahmen charakterisieren lassen. Im zweiten Teil der Arbeit entwickeln wir natürliche Begriffe von Automaten und Grammatiken für Dependenzstrukturen, zeigen, wie diese zu unendlichen Hierarchien immer ausdrucksmächtigerer Dependenzsprachen führen, und klassifizieren mehrere Grammatikformalismen in Bezug auf die Sprachen in diesen Hierarchien, die von ihnen charakterisiert werden können. Unsere Resultate liefern grundlegende Einsichten in das Verhältnis zwischen Dependenzstrukturen und lexikalisierten Grammatiken

Interactive Programming by Example

As of today, programming has never been so accessible. Yet, it remains a challenge for end-users: students, non-technical employees, experts in their domains outside of computer science, and so on. With its forecast potential for solving problems by only observing inputs and outputs, programming-by-example was supposed to alleviate complex tasks requiring programming for end-users. The initial ideas of macro-based editors paved the way to subsequent practical solutions, such as spreadsheet transformations from examples. Finding the right program is the core of the programming-by-example systems. However, users find it difficult to trust such generated programs. In this thesis, we contribute to proving that some forms of interaction alleviate, by having users provide examples, the problem of finding correct and reliable programs. We first report on two experiments that enable us to conjecture what kind of interaction brings benefits to programming-by-example. First, we present a new kind of game engine, Pong Designer. In this game engine, by using their finger, users program rules on the fly, by modifying the game state. We analyze its potential, and its eventual downsides that have probably prevented its wide adoption. Second, we present StriSynth, an interactive command-line tool that uses programming-by-example to transform string and collections. The resulting programs can also rename or otherwise manage files. We obtained the result that confirms that many users preferred StriSynth over usual programming languages, but would appreciate to have both. We then report on two new exciting experiments with verified results, using two forms of interaction truly benefiting programming-by-example. Third, on top of a programmingby- example-based engine for extracting structured data out of text files, in this thesis we study two interaction models implemented in a tool named FlashProg: a view of the program with notification about ambiguities, and the asking of clarification questions. In this thesis, we prove that these two interaction models enable users to perform tasks with less errors and to be more confident with the results. Last, for learning recursive tree-to-string functions (e.g., pretty-printers), in this thesis we prove that questioning breaks down the learning complexity from a cubic to a linear number of questions, in practice making programming-by-example even more accessible than regular programming. The implementation, named Prosy, could be easily added to integrated development environments