Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 144-146). Also available in electronic version.

published_or_final_version / abstract / Computer Science / Master / Master of Philosophy

Thesis (M. Phil.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Djang et al. [1998] introduced a new model of types for declarative visual programming languages (VPLs). Implicit static typing is used in their type model, in order to eliminate the programming mechanisms associated with type declarations, provide immediate visual feedback with respect to type errors and guarantee type safe programs. Their type model also evaluates types on a level of granularity that is finer than in previous approaches to types. Instead of evaluating types on the basis of abstract names, their model determines a set of operations that an object guarantees and compares this set to the set of operations this object is required to support. If the set of required operations is a subset of the set of guaranteed operations, then the object is considered type safe. This granularity provides their model with the ability to support inheritance without introducing explicit type declarations and to communicate type errors to users without requiring the user to understand a large set of terminology. These features of their model attempt to provide VPL users with more powerful programming capabilities without the introduction of a high learning curve. In this thesis, an implementation of the Djang et al.'s model of types is presented. Data structures and algorithms are developed that conform to the axioms prescribed by Djang et al. The space and time complexity analyses for our data structures and algorithms are examined. Our implementation provides new insights into the cost and performance of the Djang et al.'s type model. / Graduation date: 2000

We believe concreteness, direct manipulation and responsiveness in a visual programming language increase its usefulness. However, these characteristics present a challenge in generalizing programs for reuse, especially when concrete examples are used as one way of achieving concreteness. In this thesis, we present a technique to solve this problem by deriving generality automatically through the analysis of logical relationships among concrete program entities from the perspective of a particular computational goal. Use of this technique allows a fully general form-based program with reusable abstractions to be derived from one that was specified in terms of concrete examples and direct manipulation. Also addressed in this thesis is how to statically represent the generalized programs. In general, we address how to design better static representations. A weakness of many interactive visual programming languages is their static representations. Lack of an adequate static representation places a heavy cognitive burden on a VPL's programmers, because they must remember potentially long dynamic sequences of screen displays in order to understand a previously-written program. However, although this problem is widely acknowledged, research on how to design better static representations for interactive VPLs is still in its infancy. Building upon the cognitive dimensions developed for programming languages by cognitive psychologists Green and others, we have developed a set of concrete benchmarks for VPL designers to use when designing new static representations. These benchmarks provide design-time information that can be used to improve a VPL's static representation. / Graduation date: 1997

Most current DFVPLs support flow control to facilitate experiments and complex problems. However, current approaches in DFVPLs still remain inefficient. We show that inadequacies in existing visual programming languages may be magnified in applications involving image analysis. These include a lack of efficient communication mechanisms and strong dependency on human involvement to customise properties. For instance, properties in one computational component can not be shared for other components. Moreover, conditional expressions used in control components hold data values that are unrelated with those computational components. Furthermore, since image processing libraries usua.lly only explicitly support pipeline processing, as exemplified by the widely used Insight Toolkit for Medical Image Segmentation and Registration (ITK), a looping algorithm would be difficult to implement without a feedback mechanism supported by the visual language itself. We propose a data-flow visual programming language that encompasses several novel control constructs and parameterised computational units. These components are facilitated by a novel hybrid data-flow model. We also present several conceptual models and design alternatives for control constructs. Several mechanisms and techniques are provided to enhance data propagation for these components. We demonstrate, in an environment that utilises ITK as the underlying processing engine, that the inadequacies in existing DFVPLs can be satisfactorily addressed through the visual components proposed in this thesis.

Specifying varying speeds and temporal relationships is necessary when programming graphical animations, but support for temporal programming has usually been done by adding new language features to a Visual Programming Language (VPL), and these features must be mastered over and above the other aspects of the VPL. However, some researchers have believed that time should be able to be treated like just another dimension. In this thesis, we explore whether temporal programming can indeed be done using exactly the same devices as in spatial programming in grid-oriented VPLs. Toward this end, we provide a continuum of models aimed at this goal and discuss their advantages and disadvantages. Also, we identify core issues that help illuminate the essence of the problem. / Graduation date: 2001

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: streaming query; query processing; database. Includes bibliographical references (p. 57-59).

The prevalence of graphs in emerging applications has recently raised a lot of research interests. To acquire interesting information hidden in large graphs, tasks including link prediction, collaborative recommendation, and reputation ranking, all make use of proximities between graph nodes. The discounted hitting time (DHT), which is a random-walk similarity measure for graph node pairs, has shown to be useful in various applications. In this thesis, we examine a novel query, called the multi-way join (or n-way join), over DHT scores. Given a graph and n sets of nodes, the n-way join retrieves a ranked list of n-tuples with the k highest scores, according to some aggregation function of DHT values. By extracting such top-k results, this query enables the analysis and prediction of various complex relationships among n sets of nodes on a large graph. Since an n-way join is expensive to evaluate, we develop the Partial Join algorithm (or PJ). This solution decomposes an n-way join into a number of top-m 2-way joins, and combines their results to construct the answer of the n-way join. Since the process of PJ may necessitate the computation of top-(m + 1) 2-way joins, we study an incremental solution, which saves the trouble of recomputation and allows the results of top-(m+1) 2-way join to be derived quickly from the top-m 2-way join results earlier computed. For better performance, we further examine efficient processing algorithms and pruning techniques for 2-way joins. Through extensive experiments on three real graph datasets, we show that the proposed PJ algorithm accurately evaluates n-way joins, and is four orders of magnitude faster than basic solutions. / published_or_final_version / Computer Science / Master / Master of Philosophy

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: reordering predicates; multi-join operator; sliding windows; window predicates; join algorithm; continuous queries. Includes bibliographical references (p. 101-103).