Structural aspects of local adjunct languages

Several open problems concerning local adjunct languages are considered and solved. One of the most interesting (from a linguistic point of view) and difficult (mathematically) open problems was whether or not null symbols can be dispensed without sacrificing the weak generative capacity. This problem is solved and the answer is negative.Also considered are some problems concerning one-sided grammars, homomorphisms of languages (it is shown that local adjunct languages are not closed under homomorphism), β-linear languages and mixed adjunct grammars

Polynomial Learnability and Locality of Formal Grammars

We apply a complexity theoretic notion of feasible learnability called polynomial learnability to the evaluation of grammatical formalisms for linguistic description. We show that a novel, nontrivial constraint on the degree of locality of grammars allows not only context free languages but also a rich class of mildly context sensitive languages to be polynomially learnable. We discuss possible implications of this result to the theory of natural language acquisition

Infinite arrays and infinite computations

AbstractA complete metric topology is introduced on the set of all finite and infinite arrays and the topological properties of the space are studied. In this complete metric topology, infinite arrays are the limits of increasing sequences of finite arrays. The notion of successful infinite derivations in Generalized Context-free Kolam Array Grammars, yielding infinite arrays, is a subclass of Generalized context-free kolam array grammars. For this class, the finite array language generated by a reduced grammar in Greibach normal form and the set of infinite arrays generated by it are related through the notion of adherence

Creating and Maintaining Consistent Documents with Elucidative Development

Software systems usually consist of multiple artefacts, such as requirements, class diagrams, or source code. Documents, such as specifications and documentation, can also be viewed as artefacts. In practice, however, writing and updating documents is often neglected because it is expensive and brings no immediate benefit. Consequently, documents are often outdated and communicate wrong information about the software. The price is paid later when a software system must be maintained and much implicit knowledge that existed at the time of the original development has been lost. A simple way to keep documents up to date is generation. However, not all documents can be fully generated. Usually, at least some content must be written by a human author. This handwritten content is lost if the documents must be regenerated. In this thesis, Elucidative Development is introduced. It is an approach to create documents by partial generation. Partial generation means that some parts of the document are generated whereas others are handwritten. Elucidative Development retains manually written content when the document is regenerated. An integral part of Elucidative Development is a guidance system, which informs the author about changes in the generated content and helps him update the handwritten content.:1 Introduction 1.1 Contributions 1.2 Scope of the Thesis 1.3 Organisation 2 Problem Analysis and Solution Outline 2.1 Redundancy and Inconsistency 2.2 Improving Consistency with Partial Generation 2.3 Conclusion 3 Background 3.1 Grammar-Based Modularisation 3.2 Model-Driven Software Development 3.3 Round-Trip Engineering 3.4 Conclusion 4 Elucidative Development 4.1 General Idea and Running Example 4.2 Requirements of Elucidative Development 4.3 Structure and Basic Concepts of Elucidative Documents 4.4 Presentation Layer 4.5 Guidance 4.6 Conclusion 5 Model-Driven Elucidative Development 5.1 General Idea and Running Example 5.2 Requirements of Model-Driven Elucidative Development 5.3 Structure and Basic Concepts of Elucidative Documents in Model-Driven Elucidative Development 5.4 Guidance 5.5 Conclusion 6 Extensions of Elucidative Development 6.1 Validating XML-based Elucidative Documents 6.2 Backpropagation-Based Round-Trip Engineering for Computed Text Document Fragments 6.3 Conclusion 7 Tool Support for an Elucidative Development Environment 7.1 Managing Active References 7.2 Inserting Computed Document Fragments 7.3 Caching the Computed Document Fragments 7.4 Elucidative Document Validation with Schemas 7.5 Conclusion 8 Related Work 8.1 Related Documentation Approaches 8.2 Consistency Approaches 8.3 Compound Documents 8.4 Conclusion 9 Evaluation 9.1 Creating and Maintaining the Cool Component Specification 9.2 Creating and Maintaining the UML Specification 9.3 Feasibility Studies 9.4 Conclusion 10 ConclusionSoftwaresysteme setzen sich üblicherweise aus vielen verschiedenen Artefakten zusammen, zum Beispiel Anforderungen, Klassendiagrammen oder Quellcode. Dokumente, wie zum Beispiel Spezifikationen oder Dokumentation, können auch als Artefakte betrachtet werden. In der Praxis wird aber das Schreiben und Aktualisieren von Dokumenten oft vernachlässigt, weil es zum einen teuer ist und zum anderen keinen unmittelbaren Vorteil bringt. Dokumente sind darum häufig veraltet und vermitteln falsche Informationen über die Software. Den Preis muss man später zahlen, wenn die Software gepflegt wird, weil viel von dem impliziten Wissen, das zur Zeit der Entwicklung existierte, verloren ist. Eine einfache Möglichkeit, Dokumente aktuell zu halten, ist Generierung. Allerdings können nicht alle Dokumente generiert werden. Meist muss wenigstens ein Teil von einem Menschen geschrieben werden. Dieser handgeschriebene Inhalt geht verloren, wenn das Dokument neu generiert werden muss. In dieser Arbeit wird das Elucidative Development vorgestellt. Dabei handelt es sich um einen Ansatz zur Dokumenterzeugung mittels partieller Generierung. Das bedeutet, dass Teile eines Dokuments generiert werden und der Rest von Hand ergänzt wird. Beim Elucidative Development bleibt der handgeschriebene Inhalt bestehen, wenn das restliche Dokument neu generiert wird. Ein integraler Bestandteil von Elucidative Development ist darüber hinaus ein Hilfesystem, das den Autor über Änderungen an generiertem Inhalt informiert und ihm hilft, den handgeschriebenen Inhalt zu aktualisieren.:1 Introduction 1.1 Contributions 1.2 Scope of the Thesis 1.3 Organisation 2 Problem Analysis and Solution Outline 2.1 Redundancy and Inconsistency 2.2 Improving Consistency with Partial Generation 2.3 Conclusion 3 Background 3.1 Grammar-Based Modularisation 3.2 Model-Driven Software Development 3.3 Round-Trip Engineering 3.4 Conclusion 4 Elucidative Development 4.1 General Idea and Running Example 4.2 Requirements of Elucidative Development 4.3 Structure and Basic Concepts of Elucidative Documents 4.4 Presentation Layer 4.5 Guidance 4.6 Conclusion 5 Model-Driven Elucidative Development 5.1 General Idea and Running Example 5.2 Requirements of Model-Driven Elucidative Development 5.3 Structure and Basic Concepts of Elucidative Documents in Model-Driven Elucidative Development 5.4 Guidance 5.5 Conclusion 6 Extensions of Elucidative Development 6.1 Validating XML-based Elucidative Documents 6.2 Backpropagation-Based Round-Trip Engineering for Computed Text Document Fragments 6.3 Conclusion 7 Tool Support for an Elucidative Development Environment 7.1 Managing Active References 7.2 Inserting Computed Document Fragments 7.3 Caching the Computed Document Fragments 7.4 Elucidative Document Validation with Schemas 7.5 Conclusion 8 Related Work 8.1 Related Documentation Approaches 8.2 Consistency Approaches 8.3 Compound Documents 8.4 Conclusion 9 Evaluation 9.1 Creating and Maintaining the Cool Component Specification 9.2 Creating and Maintaining the UML Specification 9.3 Feasibility Studies 9.4 Conclusion 10 Conclusio

Learning and consistency

In designing learning algorithms it seems quite reasonable to construct them in such a way that all data the algorithm already has obtained are correctly and completely reflected in the hypothesis the algorithm outputs on these data. However, this approach may totally fail. It may lead to the unsolvability of the learning problem, or it may exclude any efficient solution of it. Therefore we study several types of consistent learning in recursion-theoretic inductive inference. We show that these types are not of universal power. We give “lower bounds ” on this power. We characterize these types by some versions of decidability of consistency with respect to suitable “non-standard ” spaces of hypotheses. Then we investigate the problem of learning consistently in polynomial time. In particular, we present a natural learning problem and prove that it can be solved in polynomial time if and only if the algorithm is allowed to work inconsistently. 1

Bimorphisms and synchronous grammars

We tend to think of the study of language as proceeding by characterizing the strings and structures of a language, and we think of natural language processing as using those structures to build systems of utility in manipulating the language. But many language-related problems are more fruitfully viewed as requiring the specification of a relation between two languages, rather than the specification of a single language. We provide a synthesis and extension of work that unifies two approaches to such language relations: the automata-theoretic approach based on tree transducers that transform trees to their counterparts in the relation, and the grammatical approach based on synchronous grammars that derive pairs of trees in the relation. In particular, we characterize synchronous tree-substitution grammars and synchronous tree-adjoining grammars in terms of bimorphisms, which have previously been used to characterize tree transducers. In the process, we provide new approaches to formalizing the various concepts: a metanotation for describing varieties of tree automata and transducers in equational terms; a rigorous formalization of tree-adjoining and tree-substitution grammars and their synchronous counterparts, using trees over ranked alphabets; and generalizations of tree-adjoining grammar allowing multiple adjunction.Engineering and Applied Science

Input and Intake in Language Acquisition

This dissertation presents an approach for a productive way forward in the study of language acquisition, sealing the rift between claims of an innate linguistic hypothesis space and powerful domain general statistical inference. This approach breaks language acquisition into its component parts, distinguishing the input in the environment from the intake encoded by the learner, and looking at how a statistical inference mechanism, coupled with a well defined linguistic hypothesis space could lead a learn to infer the native grammar of their native language. This work draws on experimental work, corpus analyses and computational models of Tsez, Norwegian and English children acquiring word meanings, word classes and syntax to highlight the need for an appropriate encoding of the linguistic input in order to solve any given problem in language acquisition