7059364
Non-uniform recursive subdivision surfaces
Doo-Sabin and Catmull-Clark subdivision surfaces are based on the notion of repeated knot insertion of uniform tensor product B-spline surfaces. This paper develops rules for non-uniform Doo-Sabin and Catmull-Clark surfaces that generalize non-uniform tensor product Bspline surfaces to arbitrary topologies. This added flexibility allows, among other things, the natural introduction of features such as cusps, creases, and darts, while elsewhere maintaining the same order of continuity as their uniform counterparts.
1474567
Interpolation over arbitrary topology meshes using a two-phase subdivision scheme
The construction of a smooth surface interpolating a mesh of arbitrary topological type is an important problem in many graphics applications. This paper presents a two-phase process, based on a topological modification of the control mesh and a subsequent Catmull-Clark subdivision, to construct a smooth surface that interpolates some or all of the vertices of a mesh with arbitrary topology. It is also possible to constrain the surface to have specified tangent planes at an arbitrary subset of the vertices to be interpolated. The method has the following features: 1) it is guaranteed to always work and the computation is numerically stable, 2) there is no need to solve a system of linear equations and the whole computation complexity is O(K) where K is the number of the vertices, and 3) each vertex can be associated with a scalar shape handle for local shape control. These features make interpolation using Catmull-Clark surfaces simple and, thus, make the new method itself suitable for interactive free-form shape design.
35877804
Bio-native Shape Modeling and Virtual Reality for Bio Education
Bio structural and functional research and education is playing an increasingly important role in today's post-genome era. Protein geometry and shape modeling is thus a fundamental issue for protein visualization. The number of protein structures determined by X-ray crystallography or Nuclear Magnetic Resonance (NMR) is expanding in an exponential rate. Recent technology advancement has also made it possible for the determination of larger and more complicated proteins structure. A generic and automatic shape modeling for protein structures is therefore highly desired for effective and efficient protein visualization. We propose a bio-native geometric modeling technique in this paper for constructing protein secondary structure. Our emphasis is placed on the shape compatibility with the protein conformation property. Efforts are also made to handle smooth sweeping for complex protein structures. We describe as well a Virtual Reality (VR) application for protein structure education based on our Bio-native shape modeling and visualization techniques developed in this work.
2546375
Knot intervals and multi-degree splines
This paper studies the merits of using knot interval notation for B-spline curves, and presents formulae in terms of knot intervals for common B-spline operations such as knot insertion, differentiation, and degree elevation. Using knot interval notation, the paper introduces MD-splines, which are B-spline-like curves that are comprised of polynomial segments of various degrees (MD stands for "multi-degree"). MD-splines are a generalization of B-spline curves in that if all curve segments in an MD-spline have the same degree, it reduces to a B-spline curve. The paper focuses on MD-splines of degree 1, 2, and 3, as well as degree 1 and n. MD-splines have local support, obey the convex hull and variation diminishing properties, and are at least Cn-1, where n is the smaller of the degrees of two adjoining curve segments.
35608544
Target curvature driven fairing algorithm for planar cubic B-spline curves
This paper presents a new algorithm for fairing planar cubic B-spline curves. Target curvature plots prescribed by designers according to design intent are used to identify bad points and bad curve segments. The corresponding control points are then modified using local constrained optimization. The objective function is a weighed combination of two components, which are associated with the fairness in the sense of energy minimization and the coherence to the original design, respectively. Hence, designers have more control over the fairing process by using appropriate weights for the two components. Several numerical examples are provided to demonstrate the effectiveness of the algorithm.
5971327
Approximate Implicitization Using Monoid Curves and Surfaces
Abstract This paper presents an approach to finding an approximate implicit equation and an approximate inversion map of a planar rational parametric curve or a rational parametric surface. High accuracy of the approximation is achieved with a relatively small number of low-degree curve segments or surface patches. By using monoid curves and surfaces, the method eliminates the undesirable singularities and “phantom” branches normally associated with implicit representation. The monoids are expressed in exact implicit and parametric equations simultaneously, and upper bounds are derived for the approximate errors of implicitization and inversion equations.
17318987
Applying regression test selection for COTS-based applications
ABB incorporates a variety of commercial-off-the-shelf (COTS) components in its products. When new releases of these components are made available for integration and testing, source code is often not provided. Various regression test selection processes have been developed and have been shown to be cost effectiveness. However, the majority of these test selection techniques rely on access to source code for change identification. In this paper we present the application of the lightweight Integrated - Black-box Approach for Component Change Identification (I-BACCI) Version 3 process that select regression tests for applications that use COTS components. Two case studies, examining a total of nine new component releases, were conducted at ABB on products written in C/C++ to determine the effectiveness of I-BACCI. The results of the case studies indicate this process can reduce the required number of regression tests at least 70% without sacrificing the regression fault exposure.
960732
Computing the Assignment of Orthologous Genes via Genome Rearrangement
The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics. Existing methods that assign orthologs based on the similarity between DNA or protein sequences may make erroneous assignments when sequence similarity does not clearly delineate the evolutionary relationship among genes of the same families. In this paper, we present a new approach to ortholog assignment that takes into account both sequence similarity and evolutionary events at genome level, where orthologous genes are assumed to correspond to each other in the most parsimonious evolving scenario under genome rearrangement. It is then formulated as a problem of computing the signed reversal distance with duplicates between two genomes of interest, for which an efcient heuristic algorithm was given by introducing two new optimization problems, minimum common partition and maximum cycle decomposition. Following this approach, we have implemented a high-throughput system for assigning orthologs on a genome scale, called SOAR, and tested it on both simulated data and real genome sequence data. Compared to a recent ortholog assignment method based entirely on homology search (called INPARANOID), SOAR shows a marginally better performance in terms of sensitivity on the real data set because it was able to identify several correct orthologous pairs that were missed by INPARANOID. The simulation results demonstrate that SOAR in general performs better than the iterated exemplar algorithm in terms of computing the reversal distance and assigning correct orthologs.
9909178
On the value of static analysis for fault detection in software
No single software fault-detection technique is capable of addressing all fault-detection concerns. Similarly to software reviews and testing, static analysis tools (or automated static analysis) can be used to remove defects prior to release of a software product. To determine to what extent automated static analysis can help in the economic production of a high-quality product, we have analyzed static analysis faults and test and customer-reported failures for three large-scale industrial software systems developed at Nortel Networks. The data indicate that automated static analysis is an affordable means of software fault detection. Using the orthogonal defect classification scheme, we found that automated static analysis is effective at identifying assignment and checking faults, allowing the later software production phases to focus on more complex, functional, and algorithmic faults. A majority of the defects found by automated static analysis appear to be produced by a few key types of programmer errors and some of these types have the potential to cause security vulnerabilities. Statistical analysis results indicate the number of automated static analysis faults can be effective for identifying problem modules. Our results indicate static analysis tools are complementary to other fault-detection techniques for the economic production of a high-quality software product.
17173349
A lightweight process for change identification and regression test selection in using COTS components
Various regression test selection techniques have been developed and have shown fault detection effectiveness. The majority of these test selection techniques rely on access to source code for change identification. However, when new releases of COTS components are made available for integration and testing, source code is often not available. In this paper, we present a lightweight integrated-black-box approach for component change identification (I-BACCI) process for selection of regression tests for user/glue code that uses COTS components. I-BACCI is applicable when component licensing agreements do not preclude analysis of the binary files. A case study of the process was conducted on an ABB product that uses a medium-scale internal ABB software component. Five releases of the component were examined to evaluate the efficacy of the proposed process. The result of the case study indicates this process can reduce the required number of regression tests by 54% on average.
3552947
An initial study of a lightweight process for change identification and regression test selection when source code is not available
Various regression test selection techniques have been developed and have shown to improve testing cost effectiveness via improving efficiency. The majority of these test selection techniques rely on access to source code for change identification. However, when new releases of COTS components are made available for integration and testing, source code is often not available to guide in regression test selection. In this paper we describe a lightweight integrated-black-box approach for component change identification (I-BACCI) process for selection of regression tests for user/glue code that uses COTS components. I-BACCI is applicable when component licensing agreements do not preclude binary code analysis. A case study of the process was conducted on an ABB product that uses a medium-scale internal ABB software component. Six releases of the component were examined to evaluate the efficacy of the proposed process. The result of the case study indicates that this process can reduce the required regression tests by 40% on average