Incremental Attribute Evaluation for Multi-User Semantics-Based Editors

This thesis addresses two fundamental problems associated with performing incremental attribute evaluation in multi-user editors based on the attribute grammar formalism: (1) multiple asynchronous modifications of the attributed derivation tree, and (2) segmentation of the tree into separate modular units. Solutions to these problems make it possible to construct semantics-based editors for use by teams of programmers developing or maintaining large software systems. Multi-user semantics based editors improve software productivity by reducing communication costs and snafus. The objectives of an incremental attribute evaluation algorithm for multiple asynchronous changes are that (a) all attributes of the derivation tree have correct values when evaluation terminates, and (b) the cost of evaluating attributes necessary to reestablish a correctly attributed derivation tree is minimized. We present a family of algorithms that differ in how they balance the tradeoff between algorithm efficiency and expressiveness of the attribute grammar. This is important because multi-user editors seem a practical basis for many areas of computer-supported cooperative work, not just programming. Different application areas may have distinct definitions of efficiency, and may impose different requirements on the expressiveness of the attribute grammar. The characteristics of the application domain can then be used to select the most efficient strategy for each particular editor. To address the second problem, we define an extension of classical attribute grammars that allows the specification of interface consistency checking for programs composed of many modules. Classical attribute grammars can specify the static semantics of monolithic programs or modules, but not inter-module semantics; the latter was done in the past using ad hoc techniques. Extended attribute grammars support programming-in-the-large constructs found in real programming languages, including textual inclusion, multiple kinds of modular units and nested modular units. We discuss attribute evaluation in the context of programming-in-the-large, particularly the separation of concerns between the local evaluator for each modular unit and the global evaluator that propagates attribute flows across module boundaries. The result is a uniform approach to formal specification of both intra-module and inter-module static semantic properties, with the ability to use attribute evaluation algorithms to carry out a complete static semantic analysis of a multi-module program

A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approachComment: This document corresponds to the accepted manuscript of the referenced journal articl

Code generation using a backtracking LR parser

Although the parsing phase of the modern compiler has been automated in a machine independent fashion, the diversity of computer architectures inhibits automating the code generation phase. During code generation, some intermediate representation of a source program is transformed into actual machine instructions. The need for portable compilers has driven research towards the automatic generation of code generators.;This research investigates the use of a backtracking LR parser that treats code generation as a series of tree transformations

A change-oriented architecture for mathematical authoring assistance

The computer-assisted authoring of mathematical documents using a scientific text-editor requires new mathematical knowledge management and transformation techniques to organize the overall workflow of anassistance system like the ΩMEGAsystem.The challenge is that, throughout the system, various kinds of given and derived knowledge units occur in different formats and with different dependencies. If changes occur in these pieces of knowledge, they need to be effectively propagated. We present a Change-Oriented Architecture for mathematical authoring assistance. Thereby, documents are used as interfaces and the components of the architecture interact by actively changing the interface documents and by reacting on changes. In order to optimize this style of interaction, we present two essential methods in this thesis. First, we develop an efficient method for the computation of weighted semantic changes between two versions of a document. Second, we present an invertible grammar formalism for the automated bidirectional transformation between interface documents. The presented architecture provides an adequate basis for the computer-assisted authoring of mathematical documents with semantic annotations and a controlled mathematical language

Handbook of Lexical Functional Grammar

Lexical Functional Grammar (LFG) is a nontransformational theory of linguistic structure, first developed in the 1970s by Joan Bresnan and Ronald M. Kaplan, which assumes that language is best described and modeled by parallel structures representing different facets of linguistic organization and information, related by means of functional correspondences. This volume has five parts. Part I, Overview and Introduction, provides an introduction to core syntactic concepts and representations. Part II, Grammatical Phenomena, reviews LFG work on a range of grammatical phenomena or constructions. Part III, Grammatical modules and interfaces, provides an overview of LFG work on semantics, argument structure, prosody, information structure, and morphology. Part IV, Linguistic disciplines, reviews LFG work in the disciplines of historical linguistics, learnability, psycholinguistics, and second language learning. Part V, Formal and computational issues and applications, provides an overview of computational and formal properties of the theory, implementations, and computational work on parsing, translation, grammar induction, and treebanks. Part VI, Language families and regions, reviews LFG work on languages spoken in particular geographical areas or in particular language families. The final section, Comparing LFG with other linguistic theories, discusses LFG work in relation to other theoretical approaches

Entwurf und Implementation einer auf Graph-Grammatiken beruhenden Sprache zur Funktions-Struktur-Modellierung von Pflanzen

Increasing biological knowledge requires more and more elaborate methods to translate the knowledge into executable model descriptions, and increasing computational power allows to actually execute these descriptions. Such a simulation helps to validate, extend and question the knowledge. For plant modelling, the well-established formal description language of Lindenmayer systems reaches its limits as a method to concisely represent current knowledge and to conveniently assist in current research. On one hand, it is well-suited to represent structural and geometric aspects of plant models - of which units is a plant composed, how are these connected, what is their location in 3D space -, but on the other hand, its usage to describe functional aspects - what internal processes take place in the plant structure, how does this interact with the structure - is not as convenient as desirable. This can be traced back to the underlying representation of structure as a linear chain of units, while the intrinsic nature of the structure is a tree or even a graph. Therefore, we propose to use graphs and graph grammars as a basis for plant modelling which combines structural and functional aspects. In the first part of this thesis, we develop the necessary theoretical framework. Starting with a presentation of the state of the art concerning Lindenmayer systems and graph grammars, we develop the formalism of relational growth grammars as a variant of graph grammars. We show that this formalism has a natural embedding of Lindenmayer systems which keeps all relevant properties, but represents branched structures directly as axial trees and not as linear chains with indirect encoding of branches. In the second part, we develop the main practical result, the XL programming language as an extension of the Java programming language by very general rule-based features. Short examples illustrate the application of the new language features. We describe the built-in pattern matching algorithm of the implemented run-time system for the XL programming language, and we sketch a possible implementation of an XL compiler. The third part is an application of relational growth grammars and the XL programming language. We show how the general XL interfaces can be customized for relational growth grammars. On top of this customization, several examples from a variety of disciplines demonstrate the usefulness of the developed formalism and language to describe plant growth, especially functional-structural plant models, but also artificial life, architecture or interactive games. Some examples operate on custom graphs like XML DOM trees or scene graphs of commercial 3D modellers, while the majority uses the 3D modelling platform GroIMP, a software developed in conjunction with this thesis. The appendix gives an overview of the GroIMP software. The practical usage of its plug-in for relational growth grammars is also illustrated.Das zunehmende Wissen über biologische Prozesse verlangt nach geeigneten Methoden, es in ausführbare Modelle zu übersetzen, und die zunehmende Rechenleistung der Computer ermöglicht es, diese Modelle auch tatsächlich auszuführen. Solche Simulationen dienen zur Validierung, Erweiterung und Hinterfragung des Wissens. Speziell für die Pflanzenmodellierung wurden Lindenmayer-Systeme mit Erfolg eingesetzt, jedoch stoßen diese bei aktuellen Modellierungsproblemen und Forschungsvorhaben an ihre Grenzen. Zwar sind sie gut geeignet, Pflanzenstruktur und Geometrie abzubilden - aus welchen Einheiten setzt sich eine Pflanze zusammen, wie sind diese verbunden, wie ist ihre räumliche Lage -, aber die lineare Datenstruktur erschwert die Integration von Funktionsmodellen, welche Prozesse innerhalb der verzweigten Struktur und des beanspruchten Raumes beschreiben. Daher wird in dieser Arbeit vorgeschlagen, anstelle der linearen Stuktur Graphen und Graph-Grammatiken als Grundlage für die kombinierte Funktions-Struktur-Modellierung von Pflanzen zu verwenden. Im ersten Teil der Dissertation wird der theoretische Unterbau entwickelt. Nach einer Vorstellung des aktuellen Wissensstandes auf dem Gebiet der Lindenmayer-Systeme und Graph-Grammatiken werden relationale Wachstumsgrammatiken eingeführt, die auf bekannten Mechanismen für parallele Graph-Grammatiken aufbauen und Lindenmayer-Systeme als Spezialfall enthalten, dabei jedoch verzweigte Strukturen direkt als axiale Bäume darstellen. Zur praktischen Anwendung wird im zweiten Teil die Programmiersprache XL entwickelt, die Java um allgemein gehaltene Sprachkonstrukte für Graph-Grammatiken erweitert. Kurze Beispiele zeigen die Anwendung der neuen Sprachmerkmale. Der Algorithmus zur Mustersuche wird erläutert, und die Implementation des XL-Compilers wird vorgestellt. Im dritten Teil werden mögliche Anwendungen relationaler Wachstumsgrammatiken aufgezeigt. Dazu werden zunächst die allgemeinen XL-Schnittstellen für relationale Wachstumsgrammatiken konkretisiert, um dieses System dann für Modelle aus verschiedenen Bereichen zu nutzen, darunter Funktions-Struktur-Modelle von Pflanzen, Künstliches Leben, Architektur und interaktive Spiele. Einige Beispiele nutzen spezifische Graphen wie XML-DOM-Bäume oder Szenengraphen kommerzieller 3D-Modellierprogramme, aber der überwiegende Teil baut auf der 3D-Plattform GroIMP auf, die zusammen mit dieser Dissertation entwickelt wurde. Im Anhang wird die Software GroIMP kurz vorgestellt und ihre praktische Anwendung für relationale Wachstumsgrammatiken erläutert

Corpus-consulting probabilistic approach to parsing: the CCPX parser and its complementary components

Corpus linguistics is now a major field in the study of language. In recent years corpora that are syntactically analysed have become available to researchers, and these clearly have great potential for use in the field of parsing natural language. This thesis describes a project that exploits this possibility. It makes four distinct contributions to these two fields. The first is an updated version of a corpus that is (a) analysed in terms of the rich syntax of Systemic Functional Grammar (SFG), and (b) annotated using the extensible Mark-up Language (XML). The second contribution is a native XML corpus database, and the third is a sophisticated corpus query tool for accessing it. The fourth contribution is a new type of parser that is both corpus-consulting and probabilistic. It draws its knowledge of syntactic probabilities from the corpus database, and it stores its working data within the database, so that it is strongly database-oriented. SFG has been widely used in natural language generation for approaching two decades, but it has been used far less frequently in parsing (the first stage in natural language understanding). Previous SFG corpus-based parsers have utilised traditional parsing algorithms, but they have experienced problems of efficiency and coverage, due to (a) the richness of the syntax and (b) the challenge of parsing unrestricted spoken and written texts. The present research overcomes these problems by introducing a new type of parsing algorithm that is 'semi-deterministic' (as human readers are), and utilises its knowledge of the rules—including probabilities—of English syntax. A language, however, is constantly evolving. New words and uses are added, while others become less frequent and drop out altogether. The new parsing system seeks to replicate this. As new sentences are parsed they are added to the corpus, and this slowly changes the frequencies of the words and the syntactic patterns. The corpus is in this sense dynamic, and so simulates a human's changing knowledge of words and syntax