Testing Scenario Implementation with Behavior Contracts
This paper presents behavior contracts as a new assertion mechanism and a tool that uses such contracts to support the testing of object-oriented (OO) systems. A behavior contract models how the scenarios for performing a designated task are expected to be implemented. Based on this contract, our tool can automatically monitor the program execution for checking important properties related to these scenarios. This capability can help testers to determine whether the scenarios have been implemented correctly. Our tool can also collect test coverage information w.r.t. the scenarios modeled by a behavior contract. Such information can be used to direct the testing efforts towards the less-covered scenarios, and to determine whether the implementation of these scenarios has been adequately tested. Therefore, using this tool should improve both the efficiency and effectiveness of testing OO systems

title: Test-Driven Component Integration with UML 2.0 Testing and Monitoring Profile
abstract: Test-driven development (TDD) is a software development methodology for achieving high reliability. However, the practice of TDD at the integration level is rare. In this paper, we propose a test-driven component integration approach with the support of UML 2.0 Testing and Monitoring Profile (U2TMP) that is also proposed in this paper. In our approach, automated integration-level test cases are specified using U2TMP before writing the glue-code that integrates components. U2TMP enhances UML 2.0 diagrams for specifying how test scenarios should be set up and how the integrated components are expected to interact under these scenarios. Test cases written in U2TMP can be automatically transformed into test artifacts that setup the test environment, generate test stimuli, and monitor the component interactions at runtime. These test cases serve as a guideline for writing the glue-code and a regression test- bed. With this approach, the software developers may produce glue-code of high reliability.

title: GraphScape: integrated multivariate network visualization
abstract: In this paper, we introduce a new method, GraphScape, to visualize multivariate networks, i.e., graphs with multivariate data associated with their nodes. GraphScape adopts a landscape metaphor with network structure displayed on a 2D plane and the surface height in the third dimension represents node attribute. More than one attribute can be visualized simultaneously by using multiple surfaces. In addition, GraphScape can be easily combined with existing methods to further increase the total number of attributes visualized. One of the major goals of GraphScape is to reveal multivariate graph clustering, which is based on both network structure and node attributes. This is achieved by a new layout algorithm and an innovative way of constructing attribute surface, which also allows visual clustering at different scales through interaction. A simplified attribute surface model is also proposed to reduce computation requirement when visualizing large networks. GraphScape is applied to networks of three different size (20, 100, and 1500) to demonstrate its effectiveness.

title: A Mesh Meaningful Segmentation Algorithm Using Skeleton and Minima-Rule
abstract: In this paper, a hierarchical shape decomposition algorithm is proposed, which integrates the advantages of skeleton-based and minima-rule-based meaningful segmentation algorithms. The method makes use of new geometrical and topological functions of skeleton to define initial cutting critical points, and then employs salient contours with negative minimal principal curvature values to determine natural final boundary curves among parts. And sufficient experiments have been carried out on many meshes, and shown that our framework can provide more reasonable perceptual results than single skeleton-based [8] or minima-rule-based [15] algorithm. In addition, our algorithm not only can divide a mesh of any genus into a collection of genus zero, but also partition level-of-detail meshes into similar parts.

title: Direct mesh: a multiresolution approach to terrain visualization
abstract: Terrain can be approximated by a triangular mesh consisting millions of 3D points. Multiresolution triangular mesh (MTM) structures are designed to support applications that use terrain data at variable levels of detail (LOD). Typically, an MTM adopts a tree structure where a parent node represents a lower-resolution approximation of its descendants. Given a region of interest (ROI) and a LOD, the process of retrieving the required terrain data from the database is to traverse the MTM tree from the root to reach all the nodes satisfying the ROI and LOD conditions. This process, while being commonly used for multiresolution terrain visualization, is inefficient as either a large number of sequential I/O operations or fetching a large amount of extraneous data is incurred. Various spatial indexes have been proposed in the past to address this problem, however level-by-level tree traversal remains a common practice in order to obtain topological information among the retrieved terrain data. A new MTM data structure called direct mesh is proposed. We demonstrate that with direct mesh the amount of data retrieval can be substantially reduced. Comparing with existing MTM indexing methods, a significant performance improvement has been observed for real-life terrain data.

title: A multi-resolution surface distance model for k-NN query processing
abstract: A spatial k-NN query returns k nearest points in a point dataset to a given query point. To measure the distance between two points, most of the literature focuses on the Euclidean distance or the network distance. For many applications, such as wildlife movement, it is necessary to consider the surface distance, which is computed from the shortest path along a terrain surface. In this paper, we investigate the problem of efficient surface k-NN (sk-NN) query processing. This is an important yet highly challenging problem because the underlying environment data can be very large and the computational cost of finding the shortest path on a surface can be very high. To minimize the amount of surface data to be used and the cost of surface distance computation, a multi-resolution surface distance model is proposed in this paper to take advantage of monotonic distance changes when the distances are computed at different resolution levels. Based on this innovative model, sk-NN queries can be processed efficiently by accessing and processing surface data at a just-enough resolution level within a just-enough search region. Our extensive performance evaluations using real world datasets confirm the efficiency of our proposed model.

title: 2.5D Visualisation of Overlapping Biological Networks
abstract: Biological data is often structured in the form of complex interconnected networks such as protein interaction and metabolic networks. In this paper, we investigate a new problem of visualising such overlapping biological networks. Two networks overlap if they share some nodes and edges. We present an approach for constructing visualisations of two overlapping networks, based on a restricted three dimensional representation. More specifically, we use three parallel two dimensional planes placed in three dimensions to represent overlapping networks: one for each network (the top and the bottom planes) and one for the overlapping part (in the middle plane). Our method aims to achieve both drawing aesthetics (or conventions) for each individual network, and highlighting the intersection part by them. Using three biological datasets, we evaluate our visualisation design with the aim to test whether overlapping networks can support the visual analysis of heterogeneous and yet interconnected networks.